{"id":70,"date":"2017-03-28T17:06:17","date_gmt":"2017-03-28T08:06:17","guid":{"rendered":"http:\/\/www.cl.cs.okayama-u.ac.jp\/?page_id=70"},"modified":"2026-04-09T23:02:24","modified_gmt":"2026-04-09T14:02:24","slug":"publications","status":"publish","type":"page","link":"https:\/\/www.cl.cs.okayama-u.ac.jp\/?page_id=70","title":{"rendered":"Publications"},"content":{"rendered":"

\u7814\u7a76\u767a\u8868\u4e00\u89a7(List of Publications)<\/h3>\n

<\/a>Papers\u3010\u67fb\u8aad\u4ed8\u304d\u8ad6\u6587\u3011<\/h4>\n
    \n
  1. Tatsuya Katsura and Koichi Takeuchi, Adaptable Expression Search Framework with Customizable Pattern Matching for Language Studies, Information Engineering Express Vol.12, No. 1, 2026. https:\/\/doi.org\/10.52731\/iee.v12.i1.863<\/a><\/li>\n
  2. Joe Hasei, Ryuichi Nakahara, Yujiro Otsuka, Koichi Takeuchi, Yusuke Nakamura, Kunihiro Ikuta, Shuhei Osaki, Hironari Tamiya, Shinji Miwa, Shusa Ohshika, <\/span>Shunji Nishimura, Naoaki Kahara, Aki Yoshida, Hiroya Kond, <\/span>Tomohiro Fujiwara, Toshiyuki Kunisada, and Toshifumi Ozaki, <\/span>Utility of Same-Modality, Cross-Domain Transfer Learning for Malignant Bone Tumor Detection on Radiographs: A Multi-Faceted Performance Comparison with a Scratch-Trained Modelby, <\/span>\u00a0<\/span>Cancers. 2025, 17(19):3144.<\/span>\u00a0<\/span>https:\/\/www.mdpi.com\/2072-6694\/17\/19\/3144<\/a><\/li>\n
  3. Boago OKGETHENG\u3000Koichi TAKEUCHI. Japanese Essay Scoring with Generative Pre-Trained Language Models Combined with Soft Labels, IEICE TRANSACTIONS on Information\u00a0Vol.E108-D<\/span><\/a>\u00a0No.9 pp.1095-1107, <\/span>September 2025. https:\/\/doi.org\/10.1587\/transinf.2024EDP7189 <\/a><\/span><\/li>\n
  4. <\/span>\u5b5d\u58fd \u771f\u6cbb, \u7af9\u5185 \u5b54\u4e00, \u707d\u5bb3\u6642\u306e\u30af\u30ed\u30ce\u30ed\u30b8\u30fc\u306b\u5bfe\u3059\u308b\u512a\u5148\u5ea6\u63a8\u5b9a\u306b\u304a\u3051\u308b\u9806\u5e8f\u56de\u5e30\u306e\u9069\u7528, \u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a\u8ad6\u6587\u8a8c D Vol.J107-D(No.4) 255-264 2024\u5e744\u6708.\u00a0 https:\/\/doi.org\/10.14923\/transinfj.2023PDP0041<\/a><\/li>\n
  5. \u7af9\u5185 \u5b54\u4e00, \u5927\u91ce \u96c5\u5e78, \u6cc9\u4ec1 \u5b8f\u592a, \u7530\u53e3 \u96c5\u5f18, \u7a32\u7530 \u4f73\u5f66, \u98ef\u585a \u8aa0\u4e5f, \u963f\u4fdd \u9054\u5f66, \u4e0a\u7530 \u5747. \u7814\u7a76\u5229\u7528\u53ef\u80fd\u306a\u5c0f\u8ad6\u6587\u30c7\u30fc\u30bf\u306b\u57fa\u3065\u304f\u53c2\u7167\u6587\u66f8\u3092\u5229\u7528\u3057\u305f\u5c0f\u8ad6\u6587\u63a1\u70b9\u624b\u6cd5\u306e\u958b\u767a, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u8ad6\u6587\u8a8c, Vol.62, No.9, pp.1586-1604, Sep, 2021.<\/li>\n
  6. \u5ca1\u6751 \u62d3\u54c9, \u7af9\u5185 \u5b54\u4e00, \u77f3\u539f \u9756\u5f18. \u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u5229\u7528\u3057\u305f\u65e5\u672c\u8a9e\u610f\u5473\u5f79\u5272\u4ed8\u4e0e\u30e2\u30c6\u3099\u30eb\u306e\u69cb\u7bc9, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u8ad6\u6587\u8a8c, Vol.60, No.11, 2063-2074, Nov, 2019.<\/li>\n
  7. \u77f3\u539f \u9756\u5f18, \u7af9\u5185 \u5b54\u4e00. \u4fc2\u308a\u5143\u306e\u672b\u5c3e\u8868\u73fe\u306b\u7740\u76ee\u3057\u305f Hierarchical Tag Context Tree \u3092\u5229\u7528\u3057\u305f\u65e5\u672c\u8a9e\u610f\u5473\u5f79\u5272\u4ed8\u4e0e\u30b7\u30b9\u30c6\u30e0\u306e\u69cb\u7bc9, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u8ad6\u6587\u8a8c Vol.57 No.7 1611\u20131626, July, 2016.<\/li>\n
  8. Hirotsugu Minowa, Hiromi Fujimoto, Koichi Takeuchi, A Mechanical Method for Evaluating Trainee Answers in a Risk Prediction Training System Based on the 4R Method, Information Engineering Express, Vol.1, No.3, pp.59-68, 2015.<\/li>\n
  9. Emmanuel Morin, Beatrice Daille, Koichi Takeuchi and Kyo Kageura, Brains, not Brawn: The Use of “Smart” Comparable Corpora in Bilingual Terminology Mining, ACM Transactions on Speech and Language Processing, Vol. 7, No. 1, Article 1, August 2010. doi>10.1145\/1839478.1839479<\/li>\n
  10. Koichi Takeuchi and Hideyuki Takahashi, Co-clustering with Recursive Elimination for Verb Synonym Extraction from Large Text Corpus. IEICE Transactions on Information and Systems, Vol.E92-D, No.12, pp.2334-2340, Dec. 2009. (IF\u5024 0.396)<\/strong><\/li>\n
  11. Nigel Collier, Son Doan, Ai Kawazoe, Reiko Matsuda Goodwin, Mike Conway, Yoshio Tateno, Quoc-Hung Ngo, Dinh Dien, Asanee Kawtrakul, Koichi Takeuchi, Mika Shigematsu and Kiyosu Taniguchi. BioCaster: detecting public health rumors with a Web-based text mining system. Bioinformatics,Vol.24 no.24, pages 2940-2941 Oxford University Press, DOI: 10.1093\/bioinformatics\/btn534. 2008. (IF\u5024 4.328) (\u88ab\u5f15\u7528\u6570WoS 106)<\/strong><\/li>\n
  12. N. Collier, A. Kawazoe, L. Jin, M. Shigematsu, D. Dien, R. Barrero, K. Takeuchi and A. Kawtrakul, A multilingual ontology for infectious disease surveillance: rationale, design and challenges, Language Resources and Evaluation, (40), 405–413, 2006 (on line 2007.7).(IF\u5024 0.250) (\u88ab\u5f15\u7528\u6570WoS 18)<\/strong><\/li>\n
  13. \u7af9\u5185\u5b54\u4e00\uff0c\u4e7e\u5065\u592a\u90ce\uff0c\u85e4\u7530\u7be4:\u8a9e\u5f59\u6982\u5ff5\u69cb\u9020\u306b\u57fa\u3065\u304f\u65e5\u672c\u8a9e\u52d5\u8a5e\u306e\u7d71\u8a9e\u30fb\u610f \u5473\u7279\u6027\u306e\u8a18\u8ff0\uff0c\u30ec\u30ad\u30b7\u30b3\u30f3\u30d5\u30a9\u30fc\u30e9\u30e0\uff0cNo.2, pp.85-120, 2006.6.<\/li>\n
  14. \u52a0\u85e4\u6052\u662d\uff0c\u4e7e\u5065\u592a\u90ce\uff0c\u7af9\u5185\u5b54\u4e00:\u8a00\u8a9e\u60c5\u5831\u51e6\u7406\u306b\u304a\u3051\u308b\u8f9e\u66f8\u3068\u8a9e\u5f59\u6982\u5ff5\u69cb\u9020, \u30ec\u30ad\u30b7\u30b3\u30f3\u30d5\u30a9\u30fc\u30e9\u30e0\uff0cNo.2, pp.1-26, 2006.6.<\/li>\n
  15. K. Takeuchi and N. Collier, Bio-Medical Entity Extraction using Support Vector Machines, Artificial Intelligence in Medicine, vol. 33, issue 2, pages 125-137, February, 2005. (IF\u50241.882)<\/strong><\/li>\n
  16. N. Collier and K. Takeuchi, Comparison of Character-level and Part of Speech Features for Name Recognition in Biomedical Texts, Journal of Biomedical Informatics, vol. 37, issue 6, pages 423-435, December, 2004. (IF\u50241.013)<\/strong><\/li>\n
  17. \u7af9\u5185\u5b54\u4e00, \u5185\u5c71\u6e05\u5b50, \u5409\u5ca1\u771f\u6cbb, \u5f71\u6d66\u5ce1, \u5c0f\u5c71\u7167\u592b: \u8a9e\u5f59\u6982\u5ff5\u69cb\u9020\u3092\u5229\u7528\u3057\u305f\u8907\u5408\u540d\u8a5e\u5185\u306e\u4fc2\u308a\u95a2\u4fc2\u306e\u89e3\u6790, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u8ad6\u6587\u8a8c, Vol.43, No.5, pp. 1446–1456, 2002.<\/li>\n
  18. \u5185\u5c71\u6e05\u5b50, \u7af9\u5185\u5b54\u4e00, \u5409\u5ca1\u771f\u6cbb, \u5f71\u6d66\u5ce1, \u5c0f\u5c71\u7167\u592b: \u5c02\u9580\u5206\u91ce\u306b\u304a\u3051\u308b\u8907\u5408\u540d\u8a5e\u89e3\u6790\u306e\u305f\u3081\u306e\u540d\u8a5e\u6587\u6cd5\u5c5e\u6027 \u306e\u5206\u985e\u306b\u3064\u3044\u3066, \u8a08\u91cf\u56fd\u8a9e\u5b66, Vol.23, No.1, pp. 1–24, 2001.<\/li>\n
  19. K. Kageura, M. Yoshioka, K. Takeuchi, T. Koyama, K. Tsuji, and F. Yoshikane: Recent Advances in Automatic Term Recognition: Experiences from the NTCIR Workshop on Information Retrieval and Term Recognition, Terminology, Vol.6, No.2, pp. 151–173, 2000.<\/li>\n
  20. Koichi Takeuchi and Yuji Matsumoto: Japanese OCR Error Correction Using Stochastic Morphological, Analyzer and Probabilistic Word N-gram Model, International Journal of Computer Processing of Oriental Languages, Vol.13, No.1, pp. 69–82, 2000.<\/li>\n
  21. \u7af9\u5185\u5b54\u4e00, \u677e\u672c\u88d5\u6cbb:\u7d71\u8a08\u7684\u8a00\u8a9e\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305fOCR\u8aa4\u308a\u8a02\u6b63\u30b7\u30b9\u30c6\u30e0\u306e\u69cb\u7bc9, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u8ad6\u6587\u8a8c, Vol.40, No.6, pp. 2679–2689, 1999.<\/li>\n
  22. \u7af9\u5185\u5b54\u4e00, \u677e\u672c\u88d5\u6cbb: \u96a0\u308c\u30de\u30eb\u30b3\u30d5\u30e2\u30c7\u30eb\u306b\u3088\u308b\u65e5\u672c\u8a9e\u5f62\u614b\u7d20\u89e3\u6790\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u63a8\u5b9a, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u8ad6\u6587\u8a8c, Vol.38, No.3, pp. 500–509, 1997.<\/li>\n<\/ol>\n

    <\/a><\/p>\n

    <\/a>Proceedings\u3010\u56fd\u969b\u4f1a\u8b70\u3011<\/h4>\n
      \n
    1. Boago Okgetheng, Koichi Takeuchi. Automated Essay Scoring for Japanese: The Effects of Continual Pre-Training on Domain-Specific Reference Data. Proceedings of the 8th International Conference on Information and Computer Technologies, pp.265-272, 2025. https:\/\/doi.ieeecomputersociety.org\/10.1109\/ICICT64582.2025.00048<\/a><\/li>\n
    2. Boago Okgetheng, Koichi Takeuchi. Modeling Score Estimation for Japanese Essays with Generative Pre-trained Transformers, In Proceedings of\u00a0 the 7th International Conference on Natural Language and Speech Processing (ICNLSP 2024)<\/a>, pp.64-73, 2024. \u00a0https:\/\/aclanthology.org\/2024.icnlsp-1.8\/<\/a><\/li>\n
    3. Callum Kodai Tulloch and Koichi Takeuchi. Semantic Role Labeling for Japanese Using Span-Based Models, In Proceedings of the 2023 7th International Conference on Natural Language Processing and Information Retrieval, pp.161-167, December 16, Korea,\u00a0 2023. https:\/\/dl.acm.org\/doi\/10.1145\/3639233.3639334<\/a><\/span><\/span><\/span><\/li>\n
    4. Shinji Koju, Koichi Takeuchi, Akihiro Watanabe, Takahiro Hirayama, Hiroyuki Nakano. Estimating Task Priority in Japanese Disaster Chronology Logs, In Proceedings of the 2023 7th International Conference on Natural Language Processing and Information Retrieval, pp.304-309, December 16, Korea,\u00a0 2023. https:\/\/dl.acm.org\/doi\/10.1145\/3639233.3639248<\/a><\/span><\/span><\/span><\/li>\n
    5. <\/span><\/span><\/span>Tatsuya Katsura and Koichi Takeuchi. A Platform for Searching Texts for Desired Expressions in a User-Editable Pattern Matching Environment for Language Learning, In Proceedings of The 14th International Congress on Advanced Applied Informatics (IIAI-AAI), 10th July (8-13, July), Koriyama, 2023.<\/li>\n
    6. Wataru Kano and Koichi Takeuchi. Data Augmentation for Question Answering Using Transformer-based VAE with Negative Sampling, In Proceedings of The 12th International Congress on Advanced Applied Informatics (IIAI-AAI), pp.467-470, 7th July (2-7, July), Kanazawa, 2022. (DOI 10.1109\/IIAIAAI55812.2022.00097)<\/li>\n
    7. Chihiro Ejima and Koichi Takeuchi. Statistical Learning Models for Japanese Essay Scoring Toward One-shot Learning, In Proceedings of The 12th International Congress on Advanced Applied Informatics (IIAI-AAI), pp.313-318, 5th July (2-7, July), Kanazawa, 2022. (DOI 10.1109\/IIAIAAI55812.2022.00070)<\/li>\n
    8. Koichi Takeuchi, Alastair Butler, Iku Nagasaki, Takuya Okamura, Prashant Pardeshi, Constructing Web-Accessible Semantic Role Labels and Frames for Japanese as Additions to the NPCMJ Parsed Corpus, In Proceedings of The 12th Language Resources and Evaluation Conference (LREC2020), pp. 3153\u20113161, 11 to 16 May, 2020.<\/li>\n
    9. Daiki Ko and Koichi Takeuchi. Evaluation of Embedded Vectors for Lexemes and Synsets Toward Expansion of Japanese WordNet, in Proceedings of The 16th International Conference of the Pacific Association for Computational Linguistics, pp.79-87, Hanoi, Viet Nam, 13th (11th-13th), October, 2019.(CORE Rank B)<\/strong><\/li>\n
    10. Takuya Okamura, Koichi Takeuchi, Yasuhiro Ishihara, Masahiro Taguchi, Yoshihiko Inada, Masaya Iizuka, Tatsuhiko Abo and Hitoshi Ueda. Improving Japanese Semantic-Role-Labeling Performance with Transfer Learning as Case for Limited Resources of Tagged Corpora on Aggregated Language, in Proceedings of The 32th International Conference of the Pacific Association for Computational Linguistics (PACLIC 32), Hong Kong, China, 1st (1-3), December, 2018. (CORE Rank B)<\/strong>https:\/\/www.aclweb.org\/anthology\/Y18-1058<\/a><\/li>\n
    11. Masayuki Ohno, Koichi Takeuchi, Kota Motojin, Masahiro Taguchi, Yoshihiko Inada, Masaya Iizuka, Tatsuhiko Abo and Hitoshi Ueda. Construction of Open Essay Writing Data and Automatic Essay Scoring System for Japanese, in Proceedings of The 15th International Conference of the Pacific Association for Computational Linguistics (PACLING2017), Yangon, Myanmar, pp.215-220, 17th (16-18), August, 2017. (CORE Rank B)<\/strong><\/li>\n
    12. Miki Iwai, Koichi Takeuchi, Kyo Kageura and Kazuya Ishibashi. A Method of Augmenting Bilingual Terminology by Taking Advantage of the Conceptual Systematicity of Terminologies, in Proceedings of the 5th International Workshop on Computational Terminology, Osaka, Japan, pp.30-40, December, 12th, 2016.<\/li>\n
    13. Yasuhiro Ishihara and Koichi Takeuchi. Japanese Semantic Role Labeling with Hierarchical Tag Context Trees, in Proceedings of The Pacific Association of Computational Linguistics (PACLING2015), Bali, Indonesia, 21th, (19-21), pp.184-189, May, 2015. (Core Rank B)<\/strong>
      \n(book) K. Hashida and A. Purwarianti (Eds.): PACLING 2015, CCIS (Comminications in Computer and Information Science) 593, pp.21-32, 2016. Springer. DOI: 10.1007\/978\/981-10-0515-2_2<\/li>\n
    14. Hirotsugu Minowa, Hiromi Fujimoto, Koichi Takeuchi, Automatic Evaluation Methods of Trainee\u2019s Answers to Develop a 4R Risk Prediction Training System, Proceedings of the 4th International Congress on Advanced Applied Informatics (IIAI AAI)(IEEE ComputerSociety), Okayama, (12-16th, July) pp. 283-286, 2015. DOI:10.1109\/IIAI-AAI.2015.301<\/li>\n
    15. Koichi Takeuchi, Masayuki Ueno and Nao Takeuchi. Annotating Semantic Role Information to Japanese Balanced Corpus, in Proceedings of MAPLEX 2015, Tendo, Japan, 10th, (9-10), February, 2015.<\/li>\n
    16. Koichi Takeuchi, Ulrich Apel, Rei Miyata, Ryo Murayama, Ryoko Adachi, Wolfgang Fanderl, Iris Vogel, Kyo Kageura, A Simple Platform for Defining Idiom Variation Matching Rules, In Proceedings of the XVI EURALEX Internatinal Congress: The User in Focus, Bolzano, Italy 16th, (15-19th), pp.399-404, 2014.<\/li>\n
    17. Rei Miyata, Ryoko Adachi, Ulrich Apel, Iris Vogel, Wolfgang Fanderl, Ryo Murayama, Koichi Takeuchi, Kyo Kageura, Proceedings of the 2nd Asia Pacific Corpus Linguistic Conference, Hong Kong, March, 7th, pp. 201-202, 2014.<\/li>\n
    18. Ryoko Adachi, Koichi Takeuchi, Ryo Murayamaa, Wolfgang Fanderl, Rei Miyata, Iris Vogel, Ulrich Apel, Kyo Kageura, Development and Use of a Platform for Defining Idiom Variation Rules, Proceedings of the 5th International Language Learning Conference (ILLC 2013), Penang, Malaysia, pp.1-19, November 2013.<\/li>\n
    19. Koichi Sato, Koichi Takeuchi and Kyo Kageura, Terminology-driven Augmentation of Bilingual Terminologies, Proceedings of the XIV Machine Translation Summit (Nice, September 2\u20136, 2013), pp.3-10.\n
      <\/div>\n<\/li>\n
    20. Teruo Koyama and Koichi Takeuchi, Enhancing Multi-word Term Extraction for Designated Theme Embedded in a Domain Corpus, In Proceedings of the 9th International Conference on Terminology and Artificial Intelligence, pp.73-79, 9th (8-9) November, 2011, Paris.<\/li>\n
    21. Koichi Takeuchi, Suguru Tsuchiyama, Masato Moriya, Yuuki Moriyasu and Koichi Satoh, Verb sense disambiguation based on thesaurus of predicate-argument structure, In Proceedings of International Conference on Knowledge Engineering and Ontology Development, pages 208-213, 26th (26-29) October, 2011, Paris. (Core Rank C)<\/strong><\/li>\n
    22. Nigel Collier, Reiko Matsuda Goodwin, John McCrae, Son Doan, Ai Kawazoe, Mike Conway, Asanee Kawtrakul, Koichi Takeuchi and Dinh Dien, An ontology-driven system for detecting global health events, COLING 2010, pages 215-222, Beijing, 24th (23-27), August, 2010. (Core Rank A)<\/strong><\/li>\n
    23. Koichi Takeuchi, Kentaro Inui, Nao Takeuchi and Atsushi Fujita, A Thesaurus of Predicate-Argument Structure for Japanese Verbs to Deal with Granularity of Verb Meanings, The 8th Workshop on Asian Language Resources, pages 1-8, Beijing, 21th (21-22) August 2010. The original pdf is on http:\/\/aclweb.org\/anthology\/W\/W10\/W10-3201.pdf<\/a>, and the revised pdf is here (a citation is revised).<\/a><\/li>\n
    24. Koichi Takeuchi, Takashi Shinnou and Nigel Collier, Bio-medical Term Extraction on Simple Rule Language, Proceedings of the 3rd International Symposium on Languages in Biology and Medicine,Posters, pages 132-134, Jeju Island, South Korea, 9th November 2009.<\/li>\n
    25. Koichi Takeuchi. Extraction of Verb Synonyms using Co-clustering Approach, In Proceedings of 2nd International Symposium on Universal Communication ISUC 2008, pp. 173-178, December 16th, 2008, in Osaka International Convention Center. (\u88ab\u5f15\u7528\u6570WoS 3)<\/strong><\/li>\n
    26. Morin, Emmanuel and Daille, Beatrice and Takeuchi, Koichi and Kageura, Kyo,Bilingual Terminology Mining – Using Brain, not brawn comparable corpora, Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics, 664–671, 26, June, 2007, Prague. (Core Rank A*)<\/strong><\/li>\n
    27. K.Takeuchi, T. Kanehila, K. Hila, T. Abekawa and K. Kageura, Flexible automatic look-up of English idiom entries in dictionaries, In Proceedings of Machine Translation Summit XI, pp.451–458, 13, September, 2007, Copenhagen.<\/li>\n
    28. A. Fujita, K. Furihata, K. Inui, Y. Matsumoto and K. Takeuchi. Paraphrasing of Japanese Light-verb Constructions Based on Lexical Conceptual Structure, Proceedings of the 2nd ACL Workshop on Multiword Expression, pp. 9-16, July 2004<\/li>\n
    29. K. Takeuchi, K. Kageura, T. Koyama, B. Daille and L. Romary. Construction of Grammar Based Term Extraction Model for Japanese, Proceedings of the 3rd International Workshop on Computational Terminology, pages 91-94, University of Geneva, Geneva Switzerland, (August, 31, 2004) <\/a><\/li>\n
    30. K.Takeuchi and N.Collier, Bio-Medical Entity Extraction using Support Vector Machines, In Proceedings of the ACL2003 Workshop on Natural Language Processing in Biomedicine, pages 57-64, Sapporo Convention Center, Sapporo, Japan, (July 7-12, 2003).<\/li>\n
    31. K.Takeuchi, K.Kageura, and T.Koyama, Deverbal Compound Noun Analysis Based on Lexical Conceptual Structure, In Proceedings of Poster\/Demo session in 41st Annual Meeting of the Association for Computational Linguistics (ACL03), pages 181-184, Sapporo Convention Center, Sapporo, Japan, (July 7-12, 2003).<\/li>\n
    32. K.Takeuchi, K.Kageura, and T.Koyama: Building Disambiguation System for Compound Noun Analysis Based on Lexical Conceptual Structure, In Proceedings of the second International Workshop on Generative Approaches to the Lexicon, pages 146–153, University of Geneva, Geneva Switzerland, (May 15-17, 2003).<\/li>\n
    33. K. Takeuchi, and N. Collier: Use of Support Vector Machines in Extended Named Entity Recognition. In 6th Conference on Natural Language Learning 2002 (CoNLL-2002), pages 119–125, Academia Sinica, Nankang, Taipei, Taiwan, (September, 2002).(Core Rank A)<\/strong><\/li>\n
    34. K.Takeuchi, K.Kageura, and T.Koyama: An LCS-based Approach for Analyzing Japanese Compound Nouns with Deverbal Heads, Second International Workshop on Computational Terminology. In Proceedings of the 2nd International Workshop on Computational Terminology (COMPUTERM2002), pages 64–70, Academia Sinica, Nankang, Taipei, Taiwan, (August, 2002).<\/li>\n
    35. M. Okada, K. Takeuchi, M. Yoshioka, K. Kageura, and T. Koyama: Defining Principled but Practically Manageable Lexical Units in Japanese Textual Corpora, Proceedings of the 6th Natural Language Processing Pacific Rim Symposium, pp. 47–53, National Center of Sciences, Tokyo, Japan, (November, 2001).<\/li>\n
    36. K. Takeuchi, K. Uchiyama, M. Yoshioka, K. Kageura, and T. Koyama, Categorising Deverbal Nouns Based on Lexical Conceptual Structure for Analysing Japanese Compounds, Proceedings of the IEEE International Conference on Systems, Man and Cybernetics 2001 (SMC 2001) Conference, pp. 904–909, Tucson Convention Center, Arizona, USA, (October, 2001).(Core Rank B)<\/strong><\/li>\n
    37. K. Takeuchi, K. Uchiyama, M. Yoshioka, K. Kageura, and T. Koyama: Analysis of Relations between Noun and Deverbal Nouns in Japanese Compounds Based on Lexical Conceptual Structure, Proceedings of Pacific Assciation for Computational Linguistics (PACLING’01), pp. 257–264, Kitakyuusyuu International Conference Center Kitakyusyuu, Kokura, Japan, (September, 2001).(Core Rank B)<\/strong><\/li>\n
    38. K. Takeuchi and Y. Matsumoto: Japanese OCR Error Correction Using Stochastic Language Models Trained on OCR Outputs, Proceedings of the 5th Natural Language Processing Pacific Rim Symposium 1999(NLPRS’99), pp. 50–55, Central Garden Hotel, Beijing, China, (November, 1999).<\/li>\n
    39. K. Takeuchi and Y. Matsumoto: Japanese OCR Error Correction Using Stochastic Morphological Analyzer and Probabilistic Word N-gram, Proceedings of the Eighteenth International Conference on Computer Processing of Oriental Languages (ICCPOL’99), pp. 415–420, The University of Tokushima, Tokushima, Japan. (March, 1999).<\/li>\n
    40. K. Takeuchi and Y. Matsumoto: HMM Parameter Learning for Japanese Morphological Analyzer, Proceedings of the 10th Pacific Asia Conference on Language Information and Computation (PACLIC 10) , pp. 163–172, City University of Hong Kong, Hong Kong, (December, 1995).(Core Rank B)<\/strong><\/li>\n<\/ol>\n

      <\/a>In books\u3010\u89e3\u8aac\u30fb\u7dcf\u8aac\u3011<\/h4>\n
        \n
      1. \u7af9\u5185\u5b54\u4e00, \u8ff0\u8a9e\u9805\u69cb\u9020\u30b7\u30bd\u30fc\u30e9\u30b9\u306e\u69cb\u7bc9\u3068\u6982\u5ff5\u4f53\u7cfb\u3092\u5229\u7528\u3057\u305f\u5c02\u9580\u7528\u8a9e\u306e\u51e6\u7406, \u60c5\u5831\u306e\u79d1\u5b66\u3068\u6280\u8853, 69\u5dfb, 9\u53f7, pp.421-426, 2019<\/li>\n
      2. Patrick Drouin, Natalia Grabar, Thierry Hamon, Kyo Kageura and Koichi Takeuchi, Computational terminology and filtering of terminological information -Introduction to the special issue-, Terminology 24:1 (2018), pp. 1\u20136, John Benjamins Publishing Company<\/li>\n
      3. \u7af9\u5185\u5b54\u4e00: \u8a9e\u5f59\u6982\u5ff5\u3068\u8ff0\u8a9e\u9805\u69cb\u9020, \u30b3\u30fc\u30d1\u30b9\u3068\u81ea\u7136\u8a00\u8a9e\u51e6\u7406, \u671d\u5009\u51fa\u7248, \u5965\u6751\u5b66\uff0c\u677e\u672c\u88d5\u6cbb (\u7de8), pp. 94-113, 2017. \u30ea\u30f3\u30af<\/a><\/li>\n
      4. Koichi Takeuchi: Thesaurus with Predicate-Argument Structure to Provide Base Framework to Determine States, Actions, and Change-of-States. pp.191-212, In Computational and Cognitive Approaches to Narratology, eds. Takashi Ogata and Taisuke Akimoto. IGI Global, July, 2016. http:\/\/www.igi-global.com\/book\/computational-cognitive-approaches-narratology\/146920 <\/a><\/li>\n
      5. \u7af9\u5185\u5b54\u4e00: \u300c\u30c6\u30ad\u30b9\u30c8\u30de\u30a4\u30cb\u30f3\u30b0\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\u300d, \u60c5\u5831\u30fb\u30b7\u30b9\u30c6\u30e0\u30bd\u30b5\u30a4\u30a8\u30c6\u30a3\u8a8c, \u7b2c19\u5dfb\u7b2c3\u53f7, p.17-18, 2014.11.<\/li>\n
      6. \u7af9\u5185\u5b54\u4e00: \u8a00\u8a9e\u60c5\u5831\u51e6\u7406\u306b\u304a\u3051\u308b\u8f9e\u66f8\u3068\u8a9e\u5f59\u6982\u5ff5\u69cb\u9020 \u8a9e\u5f59\u306e\u610f\u5473\u3068\u6587\u6cd5,\u304f\u308d\u3057\u304a\u51fa\u7248, \u7531\u672c\u967d\u5b50, \u5cb8\u672c \u79c0\u6a39 (\u7de8), pp.105-119, 2009.2<\/li>\n
      7. <\/a>\u7af9\u5185\u5b54\u4e00: \u8a00\u8a9e\u51e6\u7406\u3092\u6307\u5411\u3057\u305f\u52d5\u8a5e\u9805\u69cb\u9020\u30b7\u30bd\u30fc\u30e9\u30b9 \u6708\u520a\u8a00\u8a9e, Vol.37, No.8, 58–64, 2008.<\/li>\n
      8. Nigel Collier, Ai Kawazoe, Son Doan, Mika Shitematsu, Kiyosu Taniguchi, Lihua Jin, John McCrae, Hutchatai Chanlekha, Dinh Dien, Quoc Hung, Van Chi Nam, Koichi Takeuchi, Asanee Kawtrakul (2007), “Detecting Web rumours with a multilingual ontology supported text classification system”, Advances in Disease Surveillance, vol. 4, p. 242.<\/li>\n
      9. \u7af9\u5185\u5b54\u4e00: \u8a00\u8a9e\u5b66\u3092\u5229\u7528\u3057\u305f\u8907\u5408\u540d\u8a5e\u89e3\u6790\u30e2\u30c7\u30eb\u306e\u69cb\u7bc9, \u65e5\u672c\u8a9e\u5b66, vol. 20 pp. 28–35, December, 2001.<\/li>\n<\/ol>\n

        <\/a>Language resource, software etc.\u3010\u7279\u8a31\u30fb\u516c\u958b\u30bd\u30d5\u30c8\u30a6\u30a7\u30a2\u30fb\u4f5c\u54c1\u7b49\u3011<\/h4>\n
          \n
        1. \u52d5\u8a5e\u9805\u69cb\u9020\u30b7\u30bd\u30fc\u30e9\u30b9 (A Thesaurus of Predicate-Argument Structure for Japanese Verbs) (4425\u8a9e(7473\u8a9e\u7fa9))<\/li>\n<\/ol>\n

          <\/a>Handouts\u3010\u4e0a\u8a18\u306b\u542b\u307e\u308c\u306a\u3044\u8ad6\u6587\u30fb\u8a18\u4e8b\u30fb\u8457\u4f5c\u7269\u7b49\u3011<\/h4>\n
          <\/div>\n
            \n
          1. \u5b5d\u58fd \u771f\u6cbb, \u7af9\u5185 \u5b54\u4e00 (\u5ca1\u5c71\u5927), \u6e21\u9089 \u6681\u6d0b (\u5175\u533b), \u5e73\u5c71 \u9686\u6d69 (\u5ca1\u5c71\u5927), \u4e2d\u5c3e \u535a\u4e4b (\u884c\u5ca1\u533b\u7642\u5927)\u3001\u8c6a\u96e8\u707d\u5bb3\u306b\u304a\u3051\u308b\u30af\u30ed\u30ce\u30ed\u30b8\u30fc\u306e\u512a\u5148\u5ea6\u63a8\u5b9a\u306b\u5bfe\u3059\u308bLLM \u3092\u7528\u3044\u305f\u4fee\u6b63\u624b\u6cd5\u306e\u691c\u8a0e\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c32\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,Q9-5, pp.4377-4380, 3\u670812\u65e5(10-12), 2026<\/span><\/li>\n
          2. \u91d1 \u627f\u61b2, \u7af9\u5185 \u5b54\u4e00 (\u5ca1\u5c71\u5927)\u3001\u30b9\u30de\u30fc\u30c8\u30b0\u30e9\u30b9\u3092\u60f3\u5b9a\u3057\u305f\u8b1b\u7fa9\u88dc\u52a9\u3092\u76ee\u7684\u3068\u3057\u305f\u677f\u66f8\u6587\u5b57\u8a8d\u8b58\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c32\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,P7-15, pp.3349-3353, 3\u670812\u65e5(10-12), 2026<\/span><\/li>\n
          3. \u6210\u5ca1 \u667a\u4e5f, \u7af9\u5185 \u5b54\u4e00 (\u5ca1\u5c71\u5927)\u3001\u65e5\u672c\u8a9e\u5c0f\u8ad6\u6587\u306b\u304a\u3051\u308b\u30eb\u30fc\u30d6\u30ea\u30c3\u30af\u306b\u5bfe\u5fdc\u3057\u305f\u8a55\u4fa1\u90e8\u5206\u306eZero-shot\u4e88\u6e2c\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c32\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,P6-17, pp.2855-2860, 3\u670811\u65e5(10-12), 2026<\/span><\/li>\n
          4. \u4e2d\u539f \u9f8d\u4e00 (\u5ca1\u5c71\u5927), \u9ad8\u6a4b \u5eb7 (NEC), \u7af9\u5185 \u5b54\u4e00, \u9577\u8c37\u4e95 \u5b22 (\u5ca1\u5c71\u5927)\u3001Vibe \u30b3\u30fc\u30c7\u30a3\u30f3\u30b0\u304b\u3089\u5ba3\u8a00\u7684\u30d7\u30ed\u30b0\u30e9\u30e0\u3078\uff1a\u4f53\u9a13\u304b\u3089\u5b66\u3076\u533b\u7642\u6559\u80b2\u30a2\u30d7\u30ea\u958b\u767a\u624b\u6cd5\u306e\u63d0\u6848\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c32\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,P6-16, pp.2850-2854, 3\u670811\u65e5(10-12), 2026<\/span><\/li>\n
          5. \u84b2\u539f \u60a0\u767b, \u7af9\u5185 \u5b54\u4e00 (\u5ca1\u5c71\u5927)\u3001\u6587\u66f8\u753b\u50cf QA \u306e\u8868\u7406\u89e3\u306b\u304a\u3051\u308b\u691c\u7d22\u3068\u751f\u6210\u306b\u9069\u3057\u305f\u8868\u73fe\u5f62\u5f0f\u306e\u63d0\u6848\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c32\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,P6-13, pp.1469-1472, 3\u670811\u65e5(10-12), 2026<\/span><\/li>\n
          6. Boago Okgetheng, Koichi Takeuchi (\u5ca1\u5c71\u5927)\u3001Multi-Expert Evaluation with Chain-of-Thought Reasoning: A Mixture of Experts Approach to Automated Japanese Essay Scoring\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c32\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,TS4-6, pp.2834-2838, 3\u670810\u65e5(10-12), 2026<\/span><\/li>\n
          7. \u7af9\u5185 \u5b54\u4e00\uff0c\u4e2d\u539f \u9f8d\u4e00\uff0c\u54c1\u5ca1 \u73b2\uff0c\u9577\u8c37\u4e95 \u5b22\uff0c\u8868\u3092\u542b\u3081\u305f\u533b\u7642\u30ac\u30a4\u30c9\u30e9\u30a4\u30f3\u306b\u5bfe\u3059\u308bRAG\u9069\u7528\u306e\u305f\u3081\u306e\u30c7\u30fc\u30bf\u69cb\u7bc9, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a \u60c5\u5831\u57fa\u790e\u3068\u30a2\u30af\u30bb\u30b9\u6280\u8853\u7814\u7a76\u4f1a (IFAT\u7814\u7a76\u4f1a) , \u00a02025-IFAT-159, pp.1-5,\u00a0 6\u670827\u65e5, 2025<\/span><\/li>\n
          8. \u84b2\u539f \u60a0\u767b, \u7af9\u5185 \u5b54\u4e00\u3001OCR\u3092\u5229\u7528\u3057\u305fRAG\u306b\u304a\u3051\u308bPDF\u6587\u66f8\u5185\u306e\u30bf\u30a4\u30c8\u30eb\u3084\u8868\u306e\u5229\u7528\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,Q7-7,pp.2945-2948, 3\u670812\u65e5 (11-13), 2025<\/span><\/li>\n
          9. \u5b5d\u58fd \u771f\u6cbb, \u7af9\u5185 \u5b54\u4e00\u00a0\u3001\u30cf\u30f3\u30bb\u30f3\u75c5\u56de\u5fa9\u8005\u306e\u8a9e\u308a\u90e8\u306e\u8a3c\u8a00\u8a18\u9332\u306b\u5bfe\u3059\u308b\u8cea\u554f\u5fdc\u7b54\u30b7\u30b9\u30c6\u30e0\u69cb\u7bc9\u306b\u5411\u3051\u305f\u30d9\u30af\u30c8\u30eb\u691c\u7d22\u7cbe\u5ea6\u306e\u691c\u8a3c\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,Q7-4,pp.2930-2933,3\u670812\u65e5(11-13),2025<\/span><\/li>\n
          10. \u6210\u5ca1 \u667a\u4e5f, \u7af9\u5185 \u5b54\u4e00\u3001\u30eb\u30fc\u30d6\u30ea\u30c3\u30af\u306b\u57fa\u3065\u3044\u305f\u30bf\u30b0\u3092\u4ed8\u4e0e\u3057\u305f\u65e5\u672c\u8a9e\u5c0f\u8ad6\u6587\u30c7\u30fc\u30bf\u306e\u69cb\u7bc9\u3068\u81ea\u52d5\u63a1\u70b9\u3078\u306e\u52b9\u679c\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,P6-12,pp.2539-2343,3\u670812\u65e5(11-13),2025<\/span><\/li>\n
          11. \u4e2d\u539f \u9f8d\u4e00, \u7af9\u5185 \u5b54\u4e00 , \u7247\u5ca1 \u88d5\u96c4, \u54c1\u5ddd \u653f\u592a\u6717 , \u9ad8\u6a4b \u5eb7 , \u7b20\u4e95 \u8061 , \u9577\u8c37\u4e95 \u5b22, \u4e8c\u5ddd \u6469\u5468 , \u5927\u6238 \u5f70\u4e09 , \u52a0\u85e4 \u76f4\u4eba, \u938c\u5009 \u82f1\u55e3\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u3092\u5916\u90e8\u304b\u3089\u8abf\u67fb\u3059\u308b\u305f\u3081\u306e\u5171\u8457\u8005\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u7528\u3044\u305f\u767a\u8868\u4e88\u7a3f\u306e\u81ea\u52d5\u5730\u56f3\u4f5c\u6210\u306e\u8a66\u307f\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,P6-2,pp.2350-2353,3\u670812\u65e5(11-13),2025<\/span><\/li>\n
          12. \u5cf6\u7530 \u512a\u6597, \u7af9\u5185 \u5b54\u4e00\u3001\u5927\u898f\u6a21\u8a00\u8a9e\u30e2\u30c7\u30eb\u3092\u5229\u7528\u3057\u305fnetlist\u306b\u3088\u308b\u56de\u8def\u751f\u6210\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,Q4-8,pp.1650-1651,3\u670811\u65e5(11-13),2025<\/span><\/li>\n
          13. \u68ee\u672c \u4ec1, \u7af9\u5185 \u5b54\u4e00\u3001\u65e5\u672c\u8a9e\u5c0f\u8ad6\u6587\u81ea\u52d5\u63a1\u70b9\u30b7\u30b9\u30c6\u30e0\u306b\u95a2\u3059\u308b\u753b\u50cf\u30c7\u30fc\u30bf\u306e\u6d3b\u7528\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,Q3-21,pp.1293-1296,3\u670811\u65e5(11-13),2025<\/span><\/li>\n
          14. \u85e4\u672c \u7adc\u4e5f, \u7af9\u5185 \u5b54\u4e00\u00a0\u3001Stable Diffusion \u3092\u5229\u7528\u3057\u305f\u30b7\u30f3\u30dc\u30eb\u30de\u30fc\u30af\u753b\u50cf\u306e\u751f\u6210\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,Q3-18,pp.1278-1282,3\u670811\u65e5(11-13),2025<\/span><\/li>\n
          15. \u7027\u672c \u96bc\u77e2, \u7af9\u5185 \u5b54\u4e00\u00a0\u3001\u5927\u898f\u6a21\u8a00\u8a9e\u30e2\u30c7\u30eb\u306b\u3088\u308b\u30bb\u30ea\u30d5\u3092\u542b\u3080\u7269\u8a9e\u306e\u53ef\u8996\u5316\u624b\u6cd5\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,Q3-7,pp.1214-1218,3\u670811\u65e5(11-13),2025<\/span><\/li>\n
          16. \u6c34\u91ce \u53cb\u6689, \u7af9\u5185 \u5b54\u4e00\u3001\u89e3\u91c8\u53ef\u80fd\u6027\u306e\u9ad8\u3044\u81ea\u52d5\u63a1\u70b9\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305f\u5c0f\u8ad6\u6587\u63a1\u70b9\u652f\u63f4\u30b7\u30b9\u30c6\u30e0\u306e\u69cb\u7bc9\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,P2-3,pp.600-604,3\u670811\u65e5(11-13),2025<\/span><\/li>\n
          17. Boago Okgetheng, Koichi Takeuchi\u3001Evaluating the Impact of Continual Pre-Training on Japanese Essay Scoring Tasks\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,C6-1,pp.2255-2258,3\u670812\u65e5(11-13),2025<\/span><\/li>\n
          18. \u66fd\u548c \u6643\u592a\u90ce, \u7af9\u5185 \u5b54\u4e00\u3001Transformer\u30c7\u30b3\u30fc\u30c0\u30e2\u30c7\u30eb\u3092\u5229\u7528\u3057\u305f\u65e5\u672c\u8a9e\u610f\u5473\u5f79\u5272\u306b\u304a\u3044\u3066\uff0c\u7279\u5fb4\u91cf\u62bd\u51fa\u4f4d\u7f6e\u304a\u3088\u3073Attention Mask\u306e\u5f62\u72b6\u304c\u4e0e\u3048\u308b\u5f71\u97ff\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c31\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,D1-2,pp.111-115,3\u670811\u65e5(11-13),2025<\/span><\/li>\n
          19. \u68ee\u672c \u4ec1, \u7af9\u5185 \u5b54\u4e00. R2BERT\u53ca\u3073ChatGPT-3.5\u3092\u5229\u7528\u3057\u305f\u65e5\u672c\u8a9e\u5c0f\u8ad6\u6587\u306e\u81ea\u52d5\u63a1\u70b9. \u7b2c155\u56de \u60c5\u5831\u57fa\u790e\u3068\u30a2\u30af\u30bb\u30b9\u6280\u8853\u7814\u7a76\u4f1a (SIG-IFAT), 2024 6\u670828\u65e5<\/li>\n
          20. \u66fd\u548c\u6643\u592a\u90ce, \u7af9\u5185\u5b54\u4e00\u3001\u65e5\u672c\u8a9e\u610f\u5473\u5f79\u5272\u30bf\u30b9\u30af\u306b\u304a\u3044\u3066\u8907\u6570TokenID\u304c\u4e0e\u3048\u308b\u5f71\u97ff\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c30\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,P6-6,pp.1661-1664,3\u670813\u65e5(12-14),2024<\/span><\/li>\n
          21. \u5b5d\u58fd\u771f\u6cbb, \u7af9\u5185\u5b54\u4e00 , \u6e21\u9089\u6681\u6d0b , \u5e73\u5c71\u9686\u6d69 , \u4e2d\u5c3e\u535a\u4e4b\u3001\u69d8\u3005\u306a\u707d\u5bb3\u30c9\u30e1\u30a4\u30f3\u306e\u30af\u30ed\u30ce\u30ed\u30b8\u30fc\u306b\u5bfe\u3059\u308b\u512a\u5148\u5ea6\u63a8\u5b9a\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c30\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,C9-4,pp.2466-2471,3\u670812\u65e5(12-14),2024<\/span><\/li>\n
          22. Okgetheng Boago, Koichi Takeuchi<\/span>\u3001Estimating Japanese Essay Grading Scores with Large Language Models\u3001\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c30\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6,B3-2,pp.643-647,3\u670814\u65e5(12-14),2024<\/span><\/li>\n
          23. \u5927\u5ca1 \u53f2\u660e\uff0c\u7af9\u5185 \u5b54\u4e00. ChatGPT\u306b\u3088\u308b\u610f\u5473\u5f79\u5272\u4ed8\u4e0e\u30b7\u30b9\u30c6\u30e0\u306e\u69cb\u7bc9. \u60c5\u5831\u51e6\u7406\u5b66\u4f1a \u7b2c153\u56de \u60c5\u5831\u57fa\u790e\u3068\u30a2\u30af\u30bb\u30b9\u6280\u8853\u7814\u7a76\u4f1a (SIG-IFAT), 12\u670820\u65e5, 2023.<\/span><\/li>\n
          24. \u677e\u6751 \u5d07\u5149, \u7af9\u5185 \u5b54\u4e00. \u533b\u7642\u4e8b\u6545\u5831\u544a\u66f8\u306b\u5bfe\u3059\u308b\u30c6\u30ad\u30b9\u30c8\u30de\u30a4\u30cb\u30f3\u30b0\u30b7\u30b9\u30c6\u30e0, \u7b2c 22 \u56de\u60c5\u5831\u79d1\u5b66\u6280\u8853\u30d5\u30a9\u30fc\u30e9\u30e0 (FIT 2023), E-040, pp.387-390, 9\u67086\u65e5 (6-8), 2023, (FIT2023\u5968\u52b1\u8cde<\/a>).\u00a0<\/span><\/li>\n
          25. \u6842 \u8fb0\u5f25, \u7af9\u5185 \u5b54\u4e00. \u30d6\u30e9\u30a6\u30b6\u4e0a\u3067\u30e6\u30fc\u30b6\u304c\u7de8\u96c6\u53ef\u80fd\u306a\u8a00\u8a9e\u30d1\u30bf\u30fc\u30f3\u30de\u30c3\u30c1\u30b7\u30b9\u30c6\u30e0\u306e\u69cb\u7bc9, \u7b2c 22 \u56de\u60c5\u5831\u79d1\u5b66\u6280\u8853\u30d5\u30a9\u30fc\u30e9\u30e0 (FIT 2023), E-008, pp.287-290, 9\u67086\u65e5 (6-8), 2023, (FIT2023\u5968\u52b1\u8cde<\/a>).\u00a0<\/span><\/li>\n
          26. \u5b5d\u58fd \u771f\u6cbb, \u7af9\u5185 \u5b54\u4e00. \u6e21\u9089 \u6681\u6d0b, \u5e73\u5c71 \u9686\u6d69, \u4e2d\u5c3e \u535a\u4e4b, \u707d\u5bb3\u767a\u751f\u6642\u306e\u30af\u30ed\u30ce\u30ed\u30b8\u30fc\u306b\u5bfe\u3059\u308b\u512a\u5148\u5ea6\u63a8\u5b9a, \u7b2c 22 \u56de\u60c5\u5831\u79d1\u5b66\u6280\u8853\u30d5\u30a9\u30fc\u30e9\u30e0 (FIT 2023), CE-003, pp.33-36, 9\u67086\u65e5 (6-8), 2023<\/span><\/li>\n
          27. \u30bf\u30ed\u30c3\u30af\u30ab\u30e9\u30e0, \u7af9\u5185\u5b54\u4e00, \u30d0\u30c8\u30e9\u30fc\u30a2\u30e9\u30b9\u30c6\u30a2, \u9577\u5d0e\u90c1, \u30d1\u30eb\u30c7\u30b7\u30d7\u30e9\u30b7\u30e3\u30f3\u30c8, \u6df1\u5c64\u5b66\u7fd2\u3092\u5229\u7528\u3057\u305f PropBank \u5f62\u5f0f\u306e\u65e5\u672c\u8a9e\u610f\u5473\u5f79\u5272\u4ed8\u4e0e\u30e2\u30c7\u30eb, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c29\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6, C10-4, pp.2419-2421, 3\u670816\u65e5(14-16),2023<\/li>\n
          28. \u5c0f\u539f\u5b5d\u4ecb, \u7f8e\u5c3e\u6a39, \u591a\u6751\u65b0\u5e73, \u4eca\u4e0a\u535a\u53f8, \u4f50\u85e4\u529f\u4e00, \u6edd\u6fa4\u4e00\u6a39, \u7af9\u5185\u5b54\u4e00. BERT\u3092\u5229\u7528\u3057\u305f\u30c1\u30e3\u30c3\u30c8\u30dc\u30c3\u30c8\u306eQ&A\u30c7\u30fc\u30bf\u81ea\u52d5\u4f5c\u6210, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c29\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6, Q2-6, pp.519-521, 3\u670814\u65e5(14-16),2023<\/li>\n
          29. \u7f8e\u5c3e\u6a39, \u5c0f\u539f\u5b5d\u4ecb, \u591a\u6751\u65b0\u5e73, \u4eca\u4e0a\u535a\u53f8, \u4f50\u85e4\u529f\u4e00, \u6edd\u6fa4\u4e00\u6a39, \u7af9\u5185\u5b54\u4e00. \u8236\u7528\u30c7\u30a3\u30fc\u30bc\u30eb\u6a5f\u95a2\u306b\u95a2\u3059\u308b\u554f\u3044\u5408\u308f\u305b\u5bfe\u5fdc\u7528\u30c1\u30e3\u30c3\u30c8\u30dc\u30c3\u30c8\u306e\u305f\u3081\u306e\u985e\u7fa9\u8a9e\u8f9e\u66f8\u306e\u81ea\u52d5\u751f\u6210, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c29\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6, Q2-5, pp.516-518, 3\u670814\u65e5(14-16), 2023<\/li>\n
          30. \u5b5d\u58fd\u771f\u6cbb, \u7af9\u5185\u5b54\u4e00, \u6e21\u9089\u6681\u6d0b\uff0c \u5e73\u5c71\u9686\u6d69\uff0c \u4e2d\u5c3e\u535a\u4e4b. \u707d\u5bb3\u533b\u7642\u306b\u304a\u3051\u308b\u30af\u30ed\u30ce\u30ed\u30b8\u30fc\u306e\u512a\u5148\u5ea6\u8b58\u5225, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a \u7b2c149\u56de \u60c5\u5831\u57fa\u790e\u3068\u30a2\u30af\u30bb\u30b9\u6280\u8853\u7814\u7a76\u4f1a (SIG-IFAT), 2\u670827\u65e5, 2023.<\/li>\n
          31. \u85e9 \u5b87\u5049\u3001\u7af9\u5185 \u5b54\u4e00. \u4e8b\u524d\u5b66\u7fd2\u6e08\u307f\u30e2\u30c7\u30eb\u3092\u5229\u7528\u3057\u305f\u65e5\u672c\u8a9e\u5c0f\u8ad6\u6587\u63a1\u70b9\u624b\u6cd5\u306e\u69cb\u7bc9. \u7b2c21\u56de\u60c5\u5831\u79d1\u5b66\u6280\u8853\u30d5\u30a9\u30fc\u30e9\u30e0\uff08FIT2022\uff09, E010, 9\u670813\u65e5(13-15), 2022.<\/li>\n
          32. \u7af9\u5185\u5b54\u4e00, \u5ca9\u672c\u6f64\u5b63, \u30d0\u30c8\u30e9\u30fc\u30fb\u30a2\u30e9\u30b9\u30c6\u30a2, \u9577\u5d0e\u90c1, \u30d1\u30eb\u30c7\u30b7\u30fb\u30d7\u30e9\u30b7\u30e3\u30f3\u30c8. \u610f\u5473\u5f79\u5272\u3068\u6982\u5ff5\u30d5\u30ec\u30fc\u30e0\u3092\u4ed8\u4e0e\u3057\u305f NPCMJ-PT \u306b\u3088\u308b \u30bf\u30b0\u306e\u63a8\u5b9a. \u60c5\u5831\u57fa\u790e\u3068\u30a2\u30af\u30bb\u30b9\u6280\u8853 (SIG-IFAT), vol. 2022-IFAT-146 (3), pp.1-5, 3\u670818\u65e5, 2022.<\/li>\n
          33. \u7af9\u5185\u5b54\u4e00\u3001\u5c71\u5d0e\u7476\u3001\u6e21\u9089\u6681\u6d0b\u3001\u5e73\u5c71\u9686\u6d69\u3001\u4e2d\u5c3e\u535a\u4e4b. \u707d\u5bb3\u533b\u7642\u306b\u304a\u3051\u308b\u30af\u30ed\u30ce\u30ed\u30b8\u30fc\u306e\u5206\u6790. \u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a\u4fe1\u5b66\u6280\u5831. 121(415) NLC2021-31, 19-23, 3\u67087\u65e5, 2022.<\/li>\n
          34. \u7af9\u5185\u5b54\u4e00, \u30a2\u30e9\u30b9\u30c6\u30a2\u30d0\u30c8\u30e9\u30fc, \u9577\u5d0e\u90c1, \u30d7\u30e9\u30b7\u30e3\u30f3\u30c8\u30d1\u30eb\u30c7\u30b7. \u8ff0\u8a9e\u306e\u6982\u5ff5\u30d5\u30ec\u30fc\u30e0\u3068PropBank\u5f62\u5f0f\u306e\u610f\u5473\u5f79\u5272\u3092\u4ed8\u4e0e\u3057\u305fNPCMJ-PT\u306e\u69cb\u7bc9\uff0c\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c28\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6, E1-2, 3\u670815\u65e5(15-17), 2022<\/li>\n
          35. \u7af9\u5185\u5b54\u4e00, \u5c0f\u7b20\u539f\u5d07, \u5ca1\u7530\u9b41\u4eba, \u4eca\u7530\u5c06\u4e5f. \u30d6\u30ed\u30c3\u30af\u5f62\u5f0f\u3092\u5229\u7528\u3057\u305f\u30d1\u30bf\u30fc\u30f3\u30de\u30c3\u30c1\u30b7\u30b9\u30c6\u30e0\u306e\u69cb\u7bc9, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a \u7b2c28\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6, E1-3, 3\u670815\u65e5(15-17), 2022<\/li>\n
          36. \u7af9\u5185\u5b54\u4e00, \u30a2\u30e9\u30b9\u30c6\u30a2\u30d0\u30c8\u30e9\u30fc, \u9577\u5d0e\u90c1, \u30d7\u30e9\u30b7\u30e3\u30f3\u30c8\u30d1\u30eb\u30c7\u30b7. \u610f\u5473\u5f79\u5272\u3068\u6982\u5ff5\u30d5\u30ec\u30fc\u30e0\u3092\u4ed8\u4e0e\u3057\u305fNPCMJ-PT\u306b\u3088\u308b\u30bf\u30b0\u306e\u63a8\u5b9a, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a \u7b2c146\u56de\u60c5\u5831\u57fa\u790e\u3068\u30a2\u30af\u30bb\u30b9\u6280\u8853\/\u7b2c124\u56de\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a\u5408\u540c\u7814\u7a76\u767a\u8868\u4f1a, 3\u670825\u65e5, 2022<\/li>\n
          37. \u5800\u6c5f\u907c\u6cb3, \u7af9\u5185\u5b54\u4e00. \u6a5f\u68b0\u5b66\u7fd2\u3092\u5229\u7528\u3057\u305f\u65e5\u672c\u8a9e\u5c0f\u8ad6\u6587\u63a1\u70b9\u624b\u6cd5\u306e\u6bd4\u8f03,
            \n\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c28\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6, G2-2, 3\u670815\u65e5(15-17), 2022<\/li>\n
          38. \u6c5f\u5cf6\u77e5\u512a, \u7af9\u5185\u5b54\u4e00. \u6a21\u7bc4\u7b54\u6848\u306e\u307f\u3092\u5229\u7528\u3057\u305f\u65e5\u672c\u8a9e\u5c0f\u8ad6\u6587\u63a1\u70b9\u652f\u63f4\u30b7\u30b9\u30c6\u30e0
            \n\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c28\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6, E4-5, 3\u670815\u65e5(15-17), 2022<\/li>\n
          39. \u52a0\u7d0d\u6e09, \u7af9\u5185\u5b54\u4e00. Sentence-BERT\u3092\u5229\u7528\u3057\u305fFAQ\u691c\u7d22\u306b\u304a\u3051\u308b\u30c7\u30fc\u30bf\u62e1\u5f35\u624b\u6cd5
            \n\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c28\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6, C7-1, 3\u670817\u65e5(15-17), 2022<\/li>\n
          40. \u7af9\u5185\u5b54\u4e00\uff0c \u5927\u91ce\u96c5\u5e78, \u6cc9\u4ec1\u5b8f\u592a, \u7530\u53e3\u96c5\u5f18, \u7a32\u7530\u4f73\u5f66, \u98ef\u585a\u8aa0\u4e5f, \u963f\u4fdd\u9054\u5f66, \u4e0a\u7530\u5747. \u6a21\u64ec\u8a66\u9a13\u306b\u3088\u308b\u7814\u7a76\u5229\u7528\u53ef\u80fd\u306a\u65e5\u672c\u8a9e\u5c0f\u8ad6\u6587\u30c7\u30fc\u30bf\u306e\u69cb\u7bc9\u3068\u63a1\u70b9, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a \u7b2c27\u56de\u5e74\u6b21\u5927\u4f1a\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7 \u300c\u6587\u7ae0\u306e\u8a55\u4fa1\u3068\u54c1\u8cea\u63a8\u5b9a\u300dWS3-3, 3\u670819\u65e5, 2021. (\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7\u30b5\u30a4\u30c8\u306b\u539f\u7a3f\u3078\u306e\u30ea\u30f3\u30af\u3042\u308a<\/a>)<\/li>\n
          41. \u6c5f\u5cf6\u77e5\u512a, \u5800\u6c5f\u907c\u6cb3, \u7af9\u5185\u5b54\u4e00. BERT \u3092\u5229\u7528\u3057\u305f\u65e5\u672c\u8a9e\u5c0f\u8ad6\u6587\u63a1\u70b9\u652f\u63f4\u30b7\u30b9\u30c6\u30e0\u306e\u691c\u8a0e, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a \u7b2c27\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6, E2-4, 3\u670816\u65e5(16-18), 2021.<\/li>\n
          42. \u5c0f\u7b20\u539f\u5d07, \u7af9\u5185\u5b54\u4e00. \u610f\u5473\u5f79\u5272\u4ed8\u4e0e\u30c6\u30ad\u30b9\u30c8\u306b\u5bfe\u3059\u308bProlog\u30d9\u30fc\u30b9\u306e\u63a2\u7d22\u6728\u306b\u3088\u308b\u8a00\u8a9e\u30d1\u30bf\u30f3\u30de\u30c3\u30c1\u30b7\u30b9\u30c6\u30e0\u69cb\u7bc9, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a \u7b2c27\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6, C5-1, 3\u670817\u65e5(16-18), 2021.<\/li>\n
          43. \u5ca1\u7530\u9b41\u4eba, \u7af9\u5185\u5b54\u4e00. Blockly\u3092\u5229\u7528\u3057\u305f\u30bf\u30b0\u4ed8\u304d\u30b3\u30fc\u30d1\u30b9\u691c\u7d22\u30d1\u30bf\u30f3\u69cb\u7bc9\u30c4\u30fc\u30eb
            \n\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a \u7b2c27\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6, D7-2, 3\u670818\u65e5(16-18), 2021.<\/li>\n
          44. \u7af9\u5185\u5b54\u4e00, \u30a2\u30e9\u30b9\u30c6\u30a2\u30d0\u30c8\u30e9\u30fc, \u9577\u5d0e\u90c1, \u30d7\u30e9\u30b7\u30e3\u30f3\u30c8\u30d1\u30eb\u30c7\u30b7. NPCMJ\u3078\u306ePropBank\u5f62\u5f0f\u306e\u610f\u5473\u5f79\u5272\u3068\u6982\u5ff5\u30d5\u30ec\u30fc\u30e0\u306e\u4ed8\u4e0e\u306e\u9032\u6357\u5831\u544a, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a \u7b2c27\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6, E8-4, 3\u670818\u65e5(16-18), 2021.<\/li>\n
          45. \u5cb8\u672c \u5ec9\uff0c \u7af9\u5185 \u5b54\u4e00. \u30d9\u30a4\u30ba\u306e\u5b9a\u7406\u3092\u5229\u7528\u3057\u305f\u65e5\u672c\u8a9e\u610f\u5473\u5f79\u5272\u4ed8\u4e0e\u30e2\u30c7\u30eb\u306e\u69cb\u7bc9, \u7b2c19\u56de\u60c5\u5831\u79d1\u5b66\u6280\u8853\u30d5\u30a9\u30fc\u30e9\u30e0 (FIT2019),169-170. 9\u67083\u65e5(1-3), 2020.<\/li>\n
          46. \u7af9\u5185 \u5b54\u4e00. NPCMJ \u306b\u5bfe\u3059\u308b PropBank \u5f62\u5f0f\u306e\u610f\u5473\u5f79\u5272\u3068 \u540d\u524d\u306e\u610f\u5473\u5f79\u5272\u4ed8\u4e0e\u306b\u304a\u3051\u308b\u8003\u5bdf, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7814\u7a76\u5831\u544a, 2020-IFAT-138(4),1-6. 3\u670827\u65e5, 2020.<\/li>\n
          47. \u7af9\u5185\u5b54\u4e00 (\u5ca1\u5c71\u5927), \u30d0\u30c8\u30e9\u30fc\u30a2\u30e9\u30b9\u30c6\u30a2 (\u5f18\u524d\u5927), \u9577\u5d0e\u90c1 (\u540d\u5927), \u30d1\u30eb\u30c7\u30b7\u30d7\u30e9\u30b7\u30e3\u30f3\u30c8. PropBank\u5f62\u5f0f\u3092\u8003\u616e\u3057\u305fNPCMJ\u306b\u5bfe\u3059\u308b\u610f\u5473\u5f79\u5272\u4ed8\u4e0e\u301c\u614b\u306e\u9055\u3044\u3068\u7d4c\u9a13\u8005\u306e\u4ed8\u4e0e\u301c, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a \u7b2c26\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6, pp.633-636, 3\u670818\u65e5(17-19\u65e5). 2020. (\u30aa\u30f3\u30e9\u30a4\u30f3)<\/li>\n
          48. \u5fb3\u539f\u751f\u8f1d, \u6751\u4e0a\u4ec1\u4e00, \u5fb3\u4e45\u96c5\u4eba, \u7af9\u5185\u5b54\u4e00. \u65e5\u82f1\u5bfe\u8a33\u30c7\u30fc\u30bf\u3068\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u6a5f\u68b0\u7ffb\u8a33\u3092\u5229\u7528\u3057\u305f\u985e\u8a9e\u8868\u73fe\u306e\u62bd\u51fa, FIT2019\u8b1b\u6f14\u8ad6\u6587\u96c6, pp.247-248, 9\u67085\u65e5(3-5), 2019, \u5ca1\u5c71.<\/li>\n
          49. \u570b\u5e9c\u5927\u8f1d, \u7af9\u5185\u5b54\u4e00. \u65e5\u672c\u8a9eWordNet\u306b\u304a\u3051\u308b\u8a9e\u7fa9\u30fb\u6982\u5ff5\u306e\u5206\u6563\u8868\u73fe\u7372\u5f97, FIT2019\u8b1b\u6f14\u8ad6\u6587\u96c6, pp.245-246, 9\u67085\u65e5(3-5), 2019, \u5ca1\u5c71.<\/li>\n
          50. \u6e05\u91ce\u5149\u96c4, \u7af9\u5185\u5b54\u4e00. \u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u5229\u7528\u3057\u305f\u65e5\u672c\u8a9e\u5c0f\u8ad6\u6587\u306e\u81ea\u52d5\u63a1\u70b9\u306e\u691c\u8a0e, FIT2019\u8b1b\u6f14\u8ad6\u6587\u96c6,pp.239-240, 9\u67084\u65e5(3-5), 2019, \u5ca1\u5c71.<\/li>\n
          51. \u7af9\u5185 \u5b54\u4e00, Alastair Butler, \u9577\u5d0e \u90c1, Prashant Pardeshi. NPCMJ\u306b\u5bfe\u3059\u308b\u8ff0\u8a9e\u9805\u69cb\u9020\u30b7\u30bd\u30fc\u30e9\u30b9\u306e\u610f\u5473\u5f79\u5272\u3068\u6982\u5ff5\u30d5\u30ec\u30fc\u30e0\u306e\u4ed8\u4e0e, \u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u7814\u7a76\u4f1a,2019-NL-241(4), 8\u670830\u65e5(29-30), 2019, \u5c0f\u6a3d.<\/li>\n
          52. Prashant Pardeshi, Kei Yoshimoto, Susanne Miyata, Koichi Takeuchi, Hideki Kishimoto, Development of a parsed corpus and its application to linguistic research and education, in The Japanese Society for Language Sciences 2019 Conference Handbook, pp.11-13, 7\u67087\u65e5(6-7), 2019, \u4ed9\u53f0.<\/li>\n
          53. \u5c0f\u7551\u53cb\u4e5f, \u7af9\u5185\u5b54\u4e00, \u5927\u91ce\u96c5\u5e78, \u6cc9\u4ec1\u5b8f\u592a, \u7530\u53e3\u96c5\u5f18, \u7a32\u7530\u4f73\u5f66, \u98ef\u585a\u8aa0\u4e5f, \u963f\u4fdd\u9054\u5f66, \u4e0a\u7530\u5747, \u5c0f\u8ad6\u6587\u63a1\u70b9\u652f\u63f4\u30b7\u30b9\u30c6\u30e0\u306b\u304a\u3051\u308b\u6587\u5b57\u8aa4\u308a\u691c\u51fa\u30e2\u30b8\u30e5\u30fc\u30eb\u306e\u69cb\u7bc9, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c25\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6, pp.807-810, 3\u670814\u65e5(12-15), 2019, \u540d\u53e4\u5c4b.<\/li>\n
          54. \u7af9\u5185\u5b54\u4e00, \u30d0\u30c8\u30e9\u30fc \u30a2\u30e9\u30b9\u30c6\u30a2, \u9577\u5d0e\u90c1, \u30db\u30fc\u30f3 \u30b9\u30c6\u30a3\u30fc\u30d6\u30f3\u30e9\u30a4\u30c8, PropBank\u30b9\u30bf\u30a4\u30eb\u306e\u610f\u5473\u5f79\u5272\u30bf\u30b0\u3092\u5c0e\u5165\u3057\u305f\u8ff0\u8a9e\u9805\u69cb\u9020\u30b7\u30bd\u30fc\u30e9\u30b9\u3068NPCMJ\u3078\u306e\u4ed8\u4e0e\u8a08\u753b, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c25\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6, pp.136-138, 3\u670813\u65e5(12-15), 2019, \u540d\u53e4\u5c4b.<\/li>\n
          55. \u25cb\u5927\u91ce\u96c5\u5e78, \u6cc9\u4ec1\u5b8f\u592a, \u7af9\u5185\u5b54\u4e00, \u5c0f\u7551\u53cb\u4e5f, \u7530\u53e3\u96c5\u5f18, \u7a32\u7530\u4f73\u5f66, \u98ef\u585a\u8aa0\u4e5f, \u963f\u4fdd\u9054\u5f66, \u4e0a\u7530\u5747\uff0c\u3000\u53c2\u7167\u30c7\u30fc\u30bf\u3068idf\u3092\u5229\u7528\u3057\u305f\u4e8b\u524d\u63a1\u70b9\u4e0d\u8981\u306a\u5c0f\u8ad6\u6587\u8a55\u4fa1\u624b\u6cd5, \u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a, NLC2018-33, pp.103-108, 2018, 12\u670812\u65e5(11-12), \u6771\u4eac.<\/li>\n
          56. \u5927\u91ce\u96c5\u5e78, \u6cc9\u4ec1\u5b8f\u592a, \u25cb\u7af9\u5185\u5b54\u4e00, \u5c0f\u7551\u53cb\u4e5f, \u7530\u53e3\u96c5\u5f18, \u7a32\u7530\u4f73\u5f66, \u98ef\u585a\u8aa0\u4e5f, \u963f\u4fdd\u9054\u5f66, \u4e0a\u7530\u5747. \u5c0f\u8ad6\u6587\u81ea\u52d5\u63a1\u70b9\u30c7\u30fc\u30bf\u69cb\u7bc9\u3068\u7406\u89e3\u529b\u304a\u3088\u3073\u59a5\u5f53\u6027\u8a55\u4fa1\u624b\u6cd5\u306e\u69cb\u7bc9, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c24\u56de\u5e74\u6b21\u5927\u4f1a, 2018, 3\u670813\u65e5(13-15), \u5ca1\u5c71<\/li>\n
          57. \u25cb\u6cc9\u4ec1\u5b8f\u592a\u30fb\u7af9\u5185\u5b54\u4e00\u30fb\u5927\u91ce\u96c5\u5e78\u30fb\u7530\u53e3\u96c5\u5f18\u30fb\u7a32\u7530\u4f73\u5f66\u30fb\u98ef\u585a\u8aa0\u4e5f\u30fb\u963f\u4fdd\u9054\u5f66\u30fb\u4e0a\u7530\u3000\u5747\uff0c\u5c0f\u8ad6\u6587\u63a1\u70b9\u652f\u63f4\u306e\u305f\u3081\u306e\u95a2\u9023\u6587\u66f8\u53d6\u5f97\u6cd5\u306e\u8003\u5bdf\uff0c\u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a \u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a, NLC2017-24, pp.47-51, 2017, 9\u67088\u65e5 (7-8\u65e5), \u6771\u4eac.<\/li>\n
          58. \u25cb\u6cb3\u6751 \u4e00\u5e0c\uff0c\u7af9\u5185 \u5b54\u4e00\uff0cHTML\u5185\u306e\u4e26\u5217\u69cb\u9020\u3092\u5229\u7528\u3057\u305fWeb\u30da\u30fc\u30b8\u4e0a\u306e\u30a4\u30d9\u30f3\u30c8\u60c5\u5831\u62bd\u51fa\uff0c\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c79\u56de\u5168\u56fd\u5927\u4f1a\uff0c7Q-08\uff0c2017, 3\u670818\u65e5 (16\u301c18\u65e5), \u540d\u53e4\u5c4b.<\/li>\n
          59. \u25cb\u5bae\u7530 \u5468\uff0c\u7af9\u5185 \u5b54\u4e00\uff0c\u7d71\u8a08\u7684\u5b66\u7fd2\u30e2\u30c7\u30eb\u3092\u5229\u7528\u3057\u305f\u65e5\u672c\u8a9e\u6163\u7528\u53e5\u306e\u610f\u5473\u7684\u66d6\u6627\u6027\u89e3\u6d88\uff0c\u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c79\u56de\u5168\u56fd\u5927\u4f1a\uff0c7Q-04\uff0c2017, 3\u670818\u65e5 (16\u301c18\u65e5), \u540d\u53e4\u5c4b.<\/li>\n
          60. \u5ca9\u4e95\u7f8e\u6a39\uff0c\u7af9\u5185\u5b54\u4e00\uff0c\u77f3\u6a4b\u548c\u4e5f\uff0c\u5f71\u6d66 \u5ce1\uff0e\u7570\u306a\u308b\u8a00\u8a9e\u9593\u306b\u304a\u3051\u308b\u5c02\u9580\u8a9e\u5f59\u306e\u4f53\u7cfb\u6027\u306e\u5bfe\u5fdc\u306e\u5206\u6790\uff0c\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c23\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6\uff0cP13-5, pp.671-674, 2017, 3\u670815\u65e5(3\/14-16), \u7b51\u6ce2.<\/li>\n
          61. \u7af9\u5185\u5b54\u4e00, \u5927\u91ce\u96c5\u5e78, \u6cc9\u4ec1\u5b8f\u592a, \u7530\u53e3\u96c5\u5f18, \u7a32\u7530\u4f73\u5f66, \u98ef\u585a\u8aa0\u4e5f, \u963f\u4fdd\u9054\u5f66, \u4e0a\u7530\u5747\uff0c\u5c0f\u8ad6\u6587\u306e\u81ea\u52d5\u63a1\u70b9\u306b\u5411\u3051\u305f\u30aa\u30fc\u30d7\u30f3\u306a\u57fa\u672c\u30c7\u30fc\u30bf\u306e\u69cb\u7bc9\u304a\u3088\u3073\u73fe\u6bb5\u968e\u3067\u306e\u81ea\u52d5\u63a1\u70b9\u624b\u6cd5\u306e\u8a55\u4fa1\uff0c\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c23\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6\uff0cE5-2, pp.839-842, 2017, 3\u670815\u65e5(3\/14-16), \u7b51\u6ce2.<\/li>\n
          62. \u7af9\u5185\u5b54\u4e00\uff0c\u540d\u8a5e\u9805\u69cb\u9020\u4ed8\u4e0e\u30c7\u30fc\u30bf\u306e\u69cb\u7bc9\uff0c\u8a00\u8a9e\u8cc7\u6e90\u6d3b\u7528\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d5\u309a\uff0cP-D-2, pp.317-323, 2017, 3\u67088\u65e5(3\/7-8), \u7acb\u5ddd.<\/li>\n
          63. \u77f3\u6a4b\u548c\u4e5f\uff0c\u5f71\u6d66 \u5ce1\uff0c\u5ca9\u4e95\u7f8e\u6a39\uff0c\u7af9\u5185\u5b54\u4e00\uff0c\u5c02\u9580\u7528\u8a9e\u8f9e\u66f8\u62e1\u5f35\u30b7\u30b9\u30c6\u30e0\u306e\u69cb\u7bc9\uff0c\u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a\u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a\uff0cpp.13-17\uff0c2017, 2\u67089\u65e5 (2\/9-10), \u5927\u962a.<\/li>\n
          64. \u9f4b\u85e4\u5f70\uff0c\u7af9\u5185\u5b54\u4e00\uff0c\u30b3\u30d4\u30e5\u30e9\u6587\u3092\u8003\u616e\u3057\u305f\u8ff0\u8a9e\u9805\u69cb\u9020\u89e3\u6790\u5668\u306b\u3088\u308b\u542b\u610f\u8a8d\u8b58\uff0c\u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a\u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a\uff0cpp.1-5\uff0c2017, 2\u67089\u65e5(2\/9-10), \u5927\u962a.<\/li>\n
          65. \u7b95\u8f2a\u5f18\u55e3\uff0c\u7af9\u5185\u5b54\u4e00\uff0c\u85e4\u672c\u5b8f\u7f8e\uff0e\u30c6\u3099\u30b7\u3099\u30bf\u30eb 4R \u8a13\u7df4\u30b7\u30b9\u30c6\u30e0\u69cb\u7bc9\u306e\u305f\u3081\u306e\u6210\u5426\u5224\u5b9a\u30b7\u30b9\u30c6\u30e0\u306e\u6700\u9069\u5316\u624b\u6cd5\u306e\u7814\u7a76\uff0cFIT2016(\u7b2c 15 \u56de\u60c5\u5831\u79d1\u5b66\u6280\u8853\u30d5\u30a9\u30fc\u30e9\u30e0)\uff0cF-006, pp.179-180\uff0c2016, 9\u67087\u65e5 (7-9\u65e5), \u5bcc\u5c71.<\/li>\n
          66. \u7af9\u5185\u5b54\u4e00\uff0c\u91d1\u5c71\u535a\uff0c\u5e02\u7028\u771e\uff0c\u698a\u525b\u53f2\uff0c\u6e21\u8fba\u6674\u5f66\uff0c\u6771\u4e2d\u7adc\u4e00\u90ce\uff0c\u5d8b\u7530\u548c\u5b5d\uff0c\u30c6\u30ad\u30b9\u30c8\u30de\u30a4\u30cb\u30f3\u30b0\u30fb\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\u3067\u306e\u767a\u8868\u5185\u5bb9\u3068\u8a00\u8a9e\u51e6\u7406\u6280\u8853, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c22\u56de\u5e74\u6b21\u5927\u4f1a\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7\u8a00\u8a9e\u51e6\u7406\u306e\u5fdc\u7528, 2016.3.11, \u4ed9\u53f0\uff0c\u6771\u5317\u5927\uff0ehttp:\/\/www.anlp.jp\/proceedings\/annual_meeting\/2016\/workshop1\/index.html<\/li>\n
          67. \u767d\u77f3\u8cb4\u5927, \u7af9\u5185\u5b54\u4e00, BACT\u3092\u5229\u7528\u3057\u305f\u65e5\u672c\u8a9e\u6163\u7528\u53e5\u610f\u5473\u66d6\u6627\u6027\u89e3\u6d88, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c22\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6, pp.1053-1056, 2016.3.10 (3.8-3.10), \u4ed9\u53f0.\u6771\u5317\u5927\uff0c<\/li>\n
          68. \u7af9\u5185\u5b54\u4e00, BCCWJ\u3078\u306e\u8ff0\u8a9e\u9805\u69cb\u9020\u30b7\u30bd\u30fc\u30e9\u30b9\u306e\u4ed8\u4e0e\u306b\u3088\u308b\u610f\u5473\u5f79\u5272\u306e\u691c\u8a0e, \u4fe1\u5b66\u6280\u5831(\u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a), pp.13-17, 2015.12.3 (12.3-12.4), \u540d\u53e4\u5c4b.<\/li>\n
          69. \u7af9\u5185\u5b54\u4e00, \u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u6307\u5411\u306b\u57fa\u3065\u304f\u8a00\u8a9e\u30a4\u30f3\u30bf\u30fc\u30d5\u30a7\u30fc\u30b9, \u3053\u3068\u3070\u5de5\u5b66\u7814\u7a76\u4f1a, 2015.9.25 (2015.9.25-26), \u76db\u5ca1.(\u30a2\u30a4\u30fc\u30ca(25), \u30d7\u30e9\u30b6\u304a\u3067\u3063\u3066(26))<\/li>\n
          70. \u7b95\u8f2a\u5f18\u55e3, \u85e4\u672c\u5b8f\u7f8e, \u7af9\u5185\u5b54\u4e00, \u30c7\u30b8\u30bf\u30eb\u5371\u967a\u4e88\u77e5\u8a13\u7df4\u30b7\u30b9\u30c6\u30e0\u958b\u767a\u306e\u305f\u3081\u306e\u56de\u7b54\u6587\u306e\u6b63\u5426\u5224\u5b9a\u30b7\u30b9\u30c6\u30e0\u306e\u958b\u767a, \u7b2c14\u56de, \u60c5\u5831\u79d1\u5b66\u6280\u8853\u30d5\u30a9\u30fc\u30e9\u30e0\uff08FIT2015), pp.353-354, 2015.9.17 (2015.9-15-17).<\/li>\n
          71. \u7af9\u5185\u5b54\u4e00, \u540d\u8a5e\u306e\u9805\u69cb\u9020\u30c7\u30fc\u30bf\u306e\u69cb\u7bc9, \u7b2c8\u56de\u30b3\u30fc\u30d1\u30b9\u65e5\u672c\u8a9e\u5b66\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7, pp.233-236, 2015.9.2 (2015.9.1-2).<\/li>\n
          72. \u7af9\u5185 \u5b54\u4e00, \u677e\u5c3e \u5f70\u609f, \u8cea\u554f\u5fdc\u7b54\u306b\u304a\u3051\u308b\u8a00\u8a9e\u7684\u306a\u77e5\u8b58\u3068\u4e00\u822c\u7684\u306a\u77e5\u8b58\u306e\u98db\u8e8d, \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a, 2015.5.30 (2015.5.30-6.2) \u306f\u3053\u3060\u3066\u672a\u6765\u5927<\/li>\n
          73. \u677e\u5c3e\u5065\u592a, \u77f3\u539f\u9756\u5f18, \u7af9\u5185\u5b54\u4e00,\u30ce\u30f3\u30d1\u30e9\u30e1\u30c8\u30ea\u30c3\u30af\u30d9\u30a4\u30ba\u306b\u3088\u308b\u610f\u5473\u5f79\u5272\u63a8\u5b9a, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c21\u56de\u5e74\u6b21\u5927\u4f1a, pp. 297-300, 2015.3.17 (2015.3.16-21)<\/li>\n
          74. \u5c0f\u5c71\u7167\u592b, \u7af9\u5185\u5b54\u4e00, \u5916\u6765\u8a9e\u306e\u6271\u3044\u3092\u8003\u616e\u3057\u305f\u65e5\u672c\u8a9e\u5c02\u9580\u6587\u66f8\u304b\u3089\u306e\u7528\u8a9e\u62bd\u51fa, pp. 632-635, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c21\u56de\u5e74\u6b21\u5927\u4f1a, 2015.3.18 (2015.3.16-21)<\/li>\n
          75. \u5c71\u7530\u7fd4\u5e73, \u77e2\u7530\u7ae3\u592a\u90ce, \u5bae\u7530\u73b2, \u7af9\u5185\u5b54\u4e00, Ulrich Apel, Wolfgang Fanderl, \u6751\u5c71\u907c, Iris Vogel, \u5f71\u6d66\u5ce1, \u65e5\u672c\u8a9e\u30a4\u30c7\u30a3\u30aa\u30e0\u7570\u5f62\u898f\u5247\u306e\u69cb\u7bc9 pp. 91-94, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c21\u56de\u5e74\u6b21\u5927\u4f1a, 2015.3.17 (2015.3.16-21)<\/li>\n
          76. \u7af9\u5185\u5b54\u4e00, \u8ff0\u8a9e\u9805\u69cb\u9020\u3092\u610f\u8b58\u3057\u305f\u540d\u8a5e\u30c7\u30fc\u30bf\u306e\u69cb\u7bc9, \u7b2c7\u56de\u30b3\u30fc\u30d1\u30b9\u65e5\u672c\u8a9e\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7\u4e88\u7a3f\u96c6<\/a>, pp143-146, 2015.3.10 (2015.3.10-11),<\/li>\n
          77. \u7af9\u5185\u5b54\u4e00, \u8ff0\u8a9e\u9805\u69cb\u9020\u30b7\u30bd\u30fc\u30e9\u30b9\u3092\u610f\u8b58\u3057\u305f\u540d\u8a5e\u306e\u610f\u5473\u69cb\u9020\u30a2\u30ce\u30c6\u30fc\u30b7\u30e7\u30f3\u306e\u305f\u3081\u306e\u540d\u8a5e\u610f\u5473\u69cb\u9020\u306e\u691c\u8a0e, \u7b2c6\u56de\u30b3\u30fc\u30d1\u30b9\u65e5\u672c\u8a9e\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7\u4e88\u7a3f\u96c6, pp.51-56, 2014.9.9 (2014.9.9-10).<\/li>\n
          78. \u7af9\u5185\u5b54\u4e00\uff0c\u77f3\u539f\u9756\u5f18\uff0c\u7af9\u5185\u5948\u592e\uff0c\u8ff0\u8a9e\u9805\u69cb\u9020\u30b7\u30bd\u30fc\u30e9\u30b9\u306b\u3088\u308b\u8ff0\u8a9e\u3068\u540d\u8a5e\u306e\u69cb\u9020\u5316, \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a, 2I5-OS-08b-1, 2014.5.13 (2014.5.12-5.15).<\/li>\n
          79. \u6d45\u91ce\u4e00\u8f1d, \u7af9\u5185\u5b54\u4e00, Web\u30da\u30fc\u30b8\u306eHTML\u69cb\u6587\u69cb\u9020\u3092\u8003\u616e\u3057\u305f\u5730\u57df\u30a4\u30d9\u30f3\u30c8\u60c5\u5831\u306e\u62bd\u51fa, pp.53-58, \u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a, <\/span>2014.6.15 (2014.6.14-15).<\/li>\n
          80. \u7af9\u5185\u5b54\u4e00, \u77f3\u539f\u9756\u5f18, \u7af9\u5185\u5948\u592e, \u8a00\u8a9e\u5b66\u306e\u77e5\u898b\u306b\u57fa\u3065\u304f\u95a2\u6570\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u5229\u7528\u3057\u305f\u8a00\u8a9e\u7406\u89e3\u30b7\u30b9\u30c6\u30e0\u306e\u69cb\u6210, pp.1031-1034, E6-2, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c20\u56de\u5e74\u6b21\u5927\u4f1a, <\/span>2014.3.20 (2014.3.17-21).<\/li>\n
          81. \u68ee\u7530\u5bdb\u9686, \u7af9\u5185\u5b54\u4e00, \u542b\u610f\u8a8d\u8b58\u306b\u304a\u3051\u308b\u4e3b\u984c\u306b\u7740\u76ee\u3057\u305f\u6587\u306e\u6bd4\u8f03\u624b\u6cd5\u306e\u691c\u8a0e, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c20\u56de\u5e74\u6b21\u5927\u4f1a, <\/span>pp.559-561, P5-14, 2014.3.19.<\/li>\n
          82. \u77f3\u539f\u9756\u5f18, \u7af9\u5185\u5b54\u4e00, \u7cfb\u5217\u30e9\u30d9\u30ea\u30f3\u30b0\u306e\u305f\u3081\u306e\u7d20\u6027\u69cb\u9020\u3068\u6587\u8108\u9577\u3092\u540c\u6642\u306b\u8003\u616e\u3057\u305f\u7d20\u6027\u62bd\u51fa, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c20\u56de\u5e74\u6b21\u5927\u4f1a, <\/span>pp.536-538, P5-8, 2014.3.19.<\/li>\n
          83. \u7af9\u5185\u5b54\u4e00, \u767d\u77f3\u8cb4\u5927 , Ulrich Apel, \u5bae\u7530\u73b2, \u8db3\u7acb\u8ad2\u5b50, Wolfgang Fanderl, \u6751\u5c71\u907c, Iris Vogel, \u5f71\u6d66\u5ce1, \u7c21\u5358\u306a\u30a4\u30c7\u30a3\u30aa\u30e0\u7570\u5f62\u898f\u5247\u306e\u4f5c\u6210: \u30d7\u30e9\u30c3\u30c8\u30d5\u30a9\u30fc\u30e0\u3068\u65e5\u672c\u8a9e\u306e\u7570\u5f62\u898f\u5247, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c20\u56de\u5e74\u6b21\u5927\u4f1a, pp.488-491, 2014.3.19.<\/span><\/li>\n
          84. \u6ff1\u7530\u5b8f\u5e73, \u7af9\u5185\u5b54\u4e00, \u5c0f\u5c71\u7167\u592b, \u7528\u8a9e\u9593\u95a2\u4fc2\u3092\u4e00\u8cab\u3057\u3066\u767b\u9332\u3067\u304d\u308b\u7528\u8a9e\u7ba1\u7406\u30b7\u30b9\u30c6\u30e0, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c20\u56de\u5e74\u6b21\u5927\u4f1a, pp.35-38, 2014.3.18.<\/span><\/span><\/li>\n
          85. \u897f\u5ddd\u55ac\u4e5f\uff0c\u7af9\u5185\u5b54\u4e00\uff0c\u97f3\u58f0\u8a8d\u8b58\u30b7\u30b9\u30c6\u30e0Julius\u3092\u5229\u7528\u3057\u305f\u5730\u57df\u540d\u8a8d\u8b58\u3078\u306e\u9069\u7528, D-14-2, \u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a\u7dcf\u5408\u5927\u4f1a 2014.3.19<\/li>\n
          86. \u7af9\u5185\u5b54\u4e00, \u77f3\u539f\u9756\u5f18, \u7af9\u5185\u5948\u592e, \u8ff0\u8a9e\u9805\u69cb\u9020\u306e\u30b7\u30bd\u30fc\u30e9\u30b9\u5206\u985e\u3068\u610f\u5473\u5f79\u5272\u306e\u8a2d\u8a08\u306b\u3064\u3044\u3066, \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a, 2D4-OS-03a-1, 2013.6.05. <\/span><\/li>\n
          87. \u7af9\u5185\u5b54\u4e00, \u4e0a\u91ce\u771f\u5e78, \u65e5\u672c\u8a9e\u30b3\u30fc\u30cf\u309a\u30b9\u306b\u5bfe\u3059\u308b\u52d5\u8a5e\u9805\u69cb\u9020\u30b7\u30bd\u30fc\u30e9\u30b9\u306e\u6982\u5ff5\u3068\u610f\u5473\u5f79\u5272\u306e\u30a2\u30ce\u30c6\u30fc\u30b7\u30e7\u30f3, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c19\u56de\u5e74\u6b21\u5927\u4f1a, pp.162-165, 2013.3.13. <\/span><\/li>\n
          88. \u5c71\u5d0e\u5143\u63ee, \u7af9\u5185\u5b54\u4e00, \u6e90\u7fd4\u4e09\u90ce, \u4eba\u624b\u306e\u898f\u5247\u69cb\u7bc9\u306b\u3088\u308b\u5c02\u9580\u7528\u8a9e\u62bd\u51fa\u306e\u7cbe\u5ea6\u6bd4\u8f03\uff0c\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c19\u56de\u5e74\u6b21\u5927\u4f1a, pp.426-429, 2013.3.14.<\/li>\n
          89. \u77f3\u539f\u9756\u5f18, \u7af9\u5185\u5b54\u4e00, \u52d5\u8a5e\u8a9e\u91c8\u6587\u3092\u5229\u7528\u3057\u305f\u52d5\u8a5e\u3068\u305d\u306e\u7d50\u679c\u72b6\u614b\u3092\u8868\u3059\u5f62\u5bb9\u52d5\u8a5e\u3068\u306e\u5bfe\u306e\u53ce\u96c6\u304a\u3088\u3073\u4eba\u624b\u306b\u3088\u308b\u6574\u7406\uff0c\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c19\u56de\u5e74\u6b21\u5927\u4f1a, pp.430-433, 2013.3.14.<\/li>\n
          90. \u4e0a\u91ce\u771f\u5e78\uff0c\u7af9\u5185\u5b54\u4e00, \u30d5\u3099\u30e9\u30a6\u30b5\u3099\u30d8\u3099\u30fc\u30b9\u306e\u52d5\u8a5e\u8a9e\u7fa9\u53ca\u3072\u3099\u610f\u5473\u5f79\u5272\u4ed8\u4e0e\u4f5c\u696d\u30b7\u30b9\u30c6\u30e0, \u7b2c3\u56de\u30b3\u30fc\u30d1\u30b9\u65e5\u672c\u8a9e\u5b66\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7\u4e88\u7a3f\u96c6, pp.363-368, 2013.3.1<\/span> (2013.2.28 – 3.1)<\/li>\n
          91. Koichi Takeuchi, Shouzaburo Minamoto, Emmanuel Planas, Teruo Koyama, Japanese Term Extraction Toward French-Japanese Bilingual Term Extraction on Wind Power Generation Domain, IEICE Tchnical Report, NLC2012-42-12, pp. 53-56, 2012.12.20.<\/li>\n
          92. \u4e0a\u91ce\u771f\u5e78\uff0c\u7af9\u5185\u5b54\u4e00, \u52d5\u8a5e\u8a9e\u7fa9\u53ca\u3073\u610f\u5473\u5f79\u5272\u4ed8\u4e0e\u4f5c\u696d\u30b7\u30b9\u30c6\u30e0\u306e\u69cb\u7bc9, \u7b2c2\u56de\u30b3\u30fc\u30d1\u30b9\u65e5\u672c\u8a9e\u5b66\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7\u4e88\u7a3f\u96c6, pp.69-76, 2012.9.6.<\/li>\n
          93. \u7af9\u5185\u5b54\u4e00\uff0c\u4e0a\u91ce\u771f\u5e78, \u8ff0\u8a9e\u6982\u5ff5\u3092\u30d9\u30fc\u30b9\u3068\u3057\u305f\u62bd\u8c61\u540d\u8a5e\u3092\u542b\u3080\u6587\u306e\u610f\u5473\u69cb\u9020\u30a2\u30ce\u30c6\u30fc\u30b7\u30e7\u30f3, \u30c6\u30ad\u30b9\u30c8\u30a2\u30ce\u30c6\u30fc\u30b7\u30e7\u30f3\u30ef\u30fc\u30af\u30b7\u30e7\u30c3\u30d7\u30fb\u30b3\u30f3\u30c6\u30b9\u30c8, 2012.8.7.<\/li>\n
          94. \u7af9\u5185\u5b54\u4e00\uff0c\u7af9\u5185\u5948\u592e\uff0c\u77f3\u539f\u9756\u5f18 \u8ff0\u8a9e\u306e\u5206\u6790\u306b\u57fa\u3065\u304f\u6587\u66f8\u89e3\u6790\u306e\u8003\u5bdf, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a, \u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u7814\u7a76\u4f1a, NL207-15, 2012.7.27.<\/li>\n
          95. Koichi Takeuchi, Construction of predicate argument structure annotator based on event type thesaurus, International Organized Session\u300cAlan Turing Year Special Session on AI Research That Can Change The World (2), JSAI2012, 3P2-IOS-2b-3, 2012.6.14.<\/li>\n
          96. \u77f3\u539f\u9756\u5f18\uff0c\u7af9\u5185\u5b54\u4e00\uff0c \u52d5\u8a5e\u3068\u305d\u306e\u7d50\u679c\u72b6\u614b\u3092\u95a2\u4fc2\u4ed8\u3051\u308b\u7d50\u679c\u72b6\u614b\u8f9e\u66f8\u306e\u69cb\u7bc9 \u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a, \u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a, NLC2011-35, pp.73-78, 2011.10.11.<\/li>\n
          97. \u571f\u5c71\u5091\uff0c\u7af9\u5185\u5b54\u4e00\uff0c \u5c11\u6570\u6b63\u89e3\u4e8b\u4f8b\u306b\u57fa\u3065\u304f\u52d5\u8a5e\u8a9e\u7fa9\u53ca\u3073\u540d\u8a5e\u610f\u5473\u5f79\u5272\u4ed8\u4e0e\u30b7\u30b9\u30c6\u30e0 \u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a, \u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a, NLC2011-34, pp.69-72, 2011.10.11.<\/li>\n
          98. \u68ee\u5b89\u7950\u6a39\uff0c\u7af9\u5185\u5b54\u4e00\uff0c \u30b5\u5909\u540d\u8a5e\u3092\u542b\u3080\u8907\u5408\u540d\u8a5e\u306e\u8a9e\u7fa9\u89e3\u6790\u30b7\u30b9\u30c6\u30e0\u53ca\u3073\u540d\u8a5e\u8f9e\u66f8\u306e\u69cb\u7bc9 \u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a, \u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a, NLC2011-31, pp.51-56, 2011.10.11.<\/li>\n
          99. \u5b88\u5c4b\u5c06\u4eba\uff0c\u7af9\u5185\u5b54\u4e00\uff0c \u7db2\u7f85\u7684\u306a\u691c\u51fa\u3092\u91cd\u8996\u3057\u305f\u7570\u5f62\u30d1\u30bf\u30fc\u30f3\u306b\u57fa\u3065\u304f\u65e5\u672c\u8a9e\u6163\u7528\u53e5\u540c\u5b9a\u30b7\u30b9\u30c6\u30e0 \u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a, \u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a, NLC2011-33, pp. 45-50, 2011.10.11.<\/li>\n
          100. \u6e90\u7fd4\u4e09\u90ce\uff0c\u7af9\u5185\u5b54\u4e00\uff0c \u7d71\u8a08\u7684\u5b66\u7fd2\u30e2\u30c7\u30eb\u3068\u30eb\u30fc\u30eb\u30d9\u30fc\u30b9\u30e2\u30c7\u30eb\u306b\u57fa\u3065\u304f\u7528\u8a9e\u62bd\u51fa\u30b7\u30b9\u30c6\u30e0\u306e\u6bd4\u8f03, \u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a, \u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a, NLC2011-28, pp.33-37, 2011.10.10.<\/li>\n
          101. \u7af9\u5185\u5b54\u4e00\uff0c \u52d5\u8a5e\u9805\u69cb\u9020\u30b7\u30bd\u30fc\u30e9\u30b9\u306e\u69cb\u7bc9, \u4eba\u5de5\u77e5\u80fd\u5b66\u4f1a\u5168\u56fd\u5927\u4f1a, \u30aa\u30fc\u30ac\u30ca\u30a4\u30ba\u30c9\u30bb\u30c3\u30b7\u30e7\u30f3OS-03 \u610f\u5473\u3068\u7406\u89e3\u306e\u30b3\u30f3\u30d4\u30e5\u30fc\u30c6\u30a3\u30f3\u30b0, 3H2-OS3-5, 2011.6.3. (\u62db\u5f85\u8b1b\u6f14) (2011.6.1-3)<\/li>\n
          102. <\/a>\u7af9\u5185\u5b54\u4e00\uff0c\u9ad8\u6a4b\u79c0\u5e78\uff0c\u5c0f\u6797\u5927\u4ecb. \u30b0\u30e9\u30d5\u306b\u57fa\u3065\u304f\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\u306b\u3088\u308b\u52d5\u8a5e\u985e\u7fa9\u8a9e\u306e\u7372\u5f97, \u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a, NLC2010-11 pp.13-18, 2010.10.23<\/li>\n
          103. \u7af9\u5185\u5b54\u4e00\uff0c\u571f\u5c71\u5091, \u5b88\u5c4b\u5c06\u4eba, \u68ee\u5b89\u7950\u6a39. \u985e\u4f3c\u3057\u305f\u52d5\u4f5c\u3084\u72b6\u6cc1\u3092\u691c\u7d22\u3059\u308b\u305f\u3081\u306e\u610f\u5473\u5f79\u5272\u53ca\u3073\u52d5\u8a5e\u8a9e\u7fa9\u4ed8\u4e0e\u30b7\u30b9\u30c6\u30e0\u306e\u69cb\u7bc9. \u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a, NLC2009-33 pp.1-6, 2010.1.25.<\/li>\n
          104. \u7af9\u5185\u5b54\u4e00\uff0c\u68ee\u672c\u771f\u4f9d\u5b50. \u52d5\u8a5e\u9805\u69cb\u9020\u30b7\u30bd\u30fc\u30e9\u30b9\u306b\u57fa\u3065\u304f\u52d5\u8a5e\u8a9e\u7fa9\u306a\u3089\u3073\u306b\u610f\u5473\u5f79\u5272\u4ed8\u4e0e\u30c7\u30fc\u30bf\u306e\u69cb\u7bc9, \u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a, NLC2009-9 pp.13-18, 2009.10.16.<\/li>\n
          105. \u65b0\u7d0d\u8cb4\u5fd7, \u7af9\u5185\u5b54\u4e00, \u30b3\u30ea\u30a2\u30fc \u30ca\u30a4\u30b8\u30a7\u30eb. SRL\u3092\u5229\u7528\u3057\u305f\u898f\u5247\u30d9\u30fc\u30b9\u306e\u611f\u67d3\u75c7\u7528\u8a9e\u62bd\u51fa, \u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a, NLC2009-7 pp.1-5, 2009.10.16.<\/li>\n
          106. <\/a>\u5c0f\u5c71 \u7167\u592b. \u7af9\u5185\u5b54\u4e00. \u5019\u88dc\u306e\u63a5\u7d9a\u95a2\u4fc2\u3092\u8003\u616e\u3057\u305f\u8907\u5408\u8a9e\u7528\u8a9e\u62bd\u51fa, \u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u7814\u7a76\u4f1a, NLC-193, pp.1-6, 2009.9.29.<\/li>\n
          107. <\/a>\u6dfa\u5229\u4fca\u4ecb, \u7af9\u5185\u5b54\u4e00, \u963f\u8fba\u5ddd\u6b66, \u5f71\u6d66\u5ce1. Web\u4e0a\u306e\u5144\u5f1f\u30da\u30fc\u30b8\u3092\u5229\u7528\u3057\u305f\u5bfe\u8a33\u6587\u66f8\u304b\u3089\u306e\u6bb5\u843d\u30a2\u30e9\u30a4\u30f3\u30e1\u30f3\u30c8, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c15\u56de\u5e74\u6b21\u5927\u4f1a, B5-4, pp.869-872, 2009.3.5.<\/li>\n
          108. <\/a>\u7530\u4e2d\u660c\u662d, \u7af9\u5185\u5b54\u4e00. \u5c0f\u898f\u6a21\u306a\u7528\u8a9e\u30ea\u30b9\u30c8\u3092\u5229\u7528\u3057\u305f\u753b\u50cf\u8aad\u5f71\u30ec\u30dd\u30fc\u30c8\u304b\u3089\u306e\u7528\u8a9e\u62bd\u51fa. \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c15\u56de\u5e74\u6b21\u5927\u4f1a, A1-1, pp.4-7, 2009.3.3.<\/li>\n
          109. <\/a>\u91d1\u672c\u8056\u4e5f, \u7af9\u5185\u5b54\u4e00. \u985e\u4f3c\u5ea6\u306e\u9ad8\u3044\u30b5\u30d6\u30af\u30e9\u30b9\u30bf\u306b\u57fa\u3065\u304f\u540d\u8a5e\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0, \u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a, \u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a, pp.31-35, 2009.1.27.<\/li>\n
          110. <\/a>\u9ad8\u6a4b\u79c0\u5e78, \u7af9\u5185\u5b54\u4e00. \u591a\u7fa9\u6027\u3092\u8003\u616e\u3057\u305f\u540c\u6642\u5171\u8d77\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\u306b\u3088\u308b\u52d5\u8a5e\u306e\u985e\u8a9e\u62bd\u51fa, \u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a, \u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a, pp.37-42, 2009.1.27.<\/li>\n
          111. <\/a>\u5c0f\u5c71\u7167\u592b, \u7af9\u5185\u5b54\u4e00. \u5f62\u614b\u7d20\u51fa\u73fe\u30d1\u30bf\u30f3\u306b\u57fa\u3065\u304f\u6587\u66f8\u96c6\u5408\u985e\u4f3c\u6027\u8a55\u4fa1, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a, \u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u7814\u7a76\u4f1a, 188-NL-2008, pp.51-56, 2008.11.19<\/li>\n
          112. <\/a>\u7af9\u5185\u5b54\u4e00, \u5c0f\u5c71\u7167\u592b. \u52d5\u8a5e\u306e\u8a9e\u7fa9\u3068\u610f\u5473\u5f79\u5272\u3092\u4ed8\u4e0e\u3057\u305f\u30bf\u30b0\u4ed8\u30b3\u30fc\u30d1\u30b9\u306e\u4f5c\u6210, \u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a, \u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a,11\u670810\u65e5, pp.19-22, 2008.<\/li>\n
          113. <\/a>\u7530\u4e2d\u660c\u662d, \u7af9\u5185\u5b54\u4e00: \u533b\u5b66\u7528\u8a9e\u8f9e\u66f8\u3067\u5b66\u7fd2\u3057\u305f\u5206\u985e\u5668\u306b\u3088\u308b\u653e\u5c04\u7dda\u8aad\u5f71\u30ec\u30dd\u30fc\u30c8\u7528\u8a9e\u306e\u5206\u985e \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c14\u56de\u5e74\u6b21\u5927\u4f1a\uff0cE1-1,3\u670818\u65e5, pp.131-134, 2008.<\/li>\n
          114. <\/a>\u7af9\u5185\u5b54\u4e00, \u4e0b\u6751\u62d3\u4e5f \u52d5\u8a5e\u8a9e\u7fa9\u3092\u63a8\u5b9a\u3059\u308b\u305f\u3081\u306e\u8a9e\u7fa9\u4ed8\u4e0e\u30b3\u30fc\u30d1\u30b9\u306e\u4f5c\u6210: \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c14\u56de\u5e74\u6b21\u5927\u4f1a\uff0cPD1-7,3\u670818\u65e5, pp.273-276, 2008.<\/li>\n
          115. \u6dfa\u5229\u4fca\u4ecb, \u7af9\u5185\u5b54\u4e00, \u963f\u8fba\u5ddd\u6b66, \u5f71\u6d66\u5ce1: Web\u4e0a\u306e\u65e2\u8a33\u6587\u66f8\u3092\u5bfe\u8c61\u3068\u3057\u305f\u6bb5\u843d\u30a2\u30e9\u30a4\u30f3\u30e1\u30f3\u30c8 \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c14\u56de\u5e74\u6b21\u5927\u4f1a\uff0cB2-8,3\u670818\u65e5, pp.337-340, 2008.<\/li>\n
          116. \u771f\u91ce\u5149\u5e73, \u7af9\u5185\u5b54\u4e00: \u9805\u95a2\u4fc2\u306b\u3042\u308b\u540d\u8a5e\u3068\u306e\u5171\u8d77\u3092\u8003\u616e\u3057\u305f\u52d5\u8a5e\u306e\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0 \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c14\u56de\u5e74\u6b21\u5927\u4f1a\uff0cB5-1,3\u670820\u65e5, pp.1033-1036, 2008.<\/li>\n
          117. \u7af9\u5185\u5b54\u4e00, \u4e7e\u5065\u592a\u90ce, \u7af9\u5185\u5948\u592e, \u85e4\u7530\u7be4: \u610f\u5473\u306e\u5305\u542b\u95a2\u4fc2\u306b\u57fa\u3065\u304f\u52d5\u8a5e\u9805\u69cb\u9020\u306e\u7d30\u5206\u985e \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c14\u56de\u5e74\u6b21\u5927\u4f1a\uff0cB5-2, 3\u670820\u65e5, pp.1037-1040, 2008.<\/li>\n
          118. \u86ed\u6d5c\u5eb7\u96c4, \u91d1\u5e73\u6602, \u5e73\u5c3e\u4e00\u6a39, \u7af9\u5185\u5b54\u4e00, \u963f\u8fba\u5ddd\u6b66, \u5f71\u6d66\u5ce1: WordNet\u3068\u540c\u97f3\u7570\u7fa9\u8a9e\u3092\u5229\u7528\u3057\u305f\u7570\u5f62\u30a4\u30c7\u30a3\u30aa\u30e0\u691c\u7d22 \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c14\u56de\u5e74\u6b21\u5927\u4f1a\uff0cB5-4, 3\u670820\u65e5, pp.1045-1048, 2008.<\/li>\n
          119. \u5c0f\u5c71\u7167\u592b\uff0c\u7af9\u5185\u5b54\u4e00: \u7528\u8a9e\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\u306b\u57fa\u3065\u304f\u90e8\u5206\u7814\u7a76\u9818\u57df\u63a8\u5b9a\u3068\u7528\u8a9e\u5206\u985e\u3001 \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u3001\u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u7814\u7a76\u4f1a, NL-183, pp.87-92, 1\u670822\u65e5, 2008.<\/li>\n
          120. \u4e00\u30ce\u702c \u5145\uff0c\u7af9\u5185 \u5b54\u4e00: \u30e1\u30bf\u30d5\u30a1\u5206\u6790\u306b\u57fa\u3065\u304f\u7f6e\u63db\u53ef\u80fd\u306a\u52d5\u8a5e\u30ab\u30c6\u30b4\u30ea\u306e\u4f5c\u6210 \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u3001\u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u7814\u7a76\u4f1a, \u9759\u5ca1, NL-182, pp.31-38, 11\u670819\u65e5, 2007.<\/li>\n
          121. \u7af9\u5185 \u5b54\u4e00: \u30b0\u30e9\u30d5\u69cb\u9020\u306b\u57fa\u3065\u304f\u540c\u6642\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\u3092\u5229\u7528\u3057\u305f\u52d5\u8a5e\u306e\u5c5e\u6027\u30af\u30e9\u30b9\u306e\u62bd\u51fa \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u3001\u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u7814\u7a76\u4f1a, \u9759\u5ca1, NL-182, pp.39-44, 11\u670819\u65e5, 2007.<\/li>\n
          122. \u5c0f\u5c71\u7167\u592b\uff0c\u7af9\u5185 \u5b54\u4e00: \u65e5\u672c\u8a9e\u8907\u5408\u8a9e\u7528\u8a9e\u306e\u5165\u308c\u5b50\u95a2\u4fc2\u306b\u57fa\u3065\u304f\u968e\u5c64\u7684\u4f53\u7cfb\u5316, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u3001\u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u7814\u7a76\u4f1a, \u5fb3\u5cf6, NL-180, pp.49-54, 7\u670824\u65e5, 2007.<\/li>\n
          123. \u7af9\u5185 \u5b54\u4e00\uff0c\u4e7e \u5065\u592a\u90ce\uff0c\u85e4\u7530 \u7be4\uff0c\u7af9\u5185 \u5948\u592e: \u8a9e\u5f59\u6982\u5ff5\u69cb\u9020\u306b\u57fa\u3065\u304f\u4e8b\u614b\u4e0a\u4f4d\u30aa\u30f3\u30c8\u30ed\u30b8\u30fc\u306e\u69cb\u7bc9 \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c13\u56de\u5e74\u6b21\u5927\u4f1a\uff0cpp. 859-862, 2007.3.22<\/li>\n
          124. \u7af9\u5185\u5b54\u4e00, \u91d1\u5e73\u6602, \u5e73\u5c3e\u4e00\u6a39, \u963f\u8fba\u5ddd\u6b66, \u5f71\u6d66\u5ce1 \u7f6e\u63db\u30fb\u633f\u5165\u3092\u8003\u616e\u3057\u305f\u7570\u5f62\u30a4\u30c7\u30a3\u30aa\u30e0\u691c\u7d22\u30b7\u30b9\u30c6\u30e0\u306e\u69cb\u7bc9 \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c13\u56de\u5e74\u6b21\u5927\u4f1a\uff0cpp. 396-399, 2007.3.20.<\/li>\n
          125. \u7af9\u5185\u5b54\u4e00, \u5ca1\u7530\u548c\u4e5f, \u5ddd\u6dfb\u611b, \u30b3\u30ea\u30a2\u30fc\u30fb\u30ca\u30a4\u30b8\u30a7\u30eb \u7d71\u8a08\u7684\u624b\u6cd5\u3092\u5229\u7528\u3057\u305f\u4f1d\u67d3\u75c5\u691c\u7d22\u30b7\u30b9\u30c6\u30e0\u306e\u69cb\u7bc9\u306b\u5411\u3051\u3066 \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c13\u56de\u5e74\u6b21\u5927\u4f1a\uff0cpp.578-581, 2007.3.21<\/li>\n
          126. \u4e7e \u5065\u592a\u90ce\uff0c\u7af9\u5185 \u5b54\u4e00\uff0c\u85e4\u7530 \u7be4: \u542b\u610f\u95a2\u4fc2\u8a08\u7b97\u306e\u305f\u3081\u306e\u4e8b\u614b\u30aa\u30f3\u30c8\u30ed\u30b8\u30fc\u306e\u958b\u767a\u306b\u5411\u3051\u3066 \u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a\uff0c\u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3\u7814\u7a76\u4f1a\uff0cNLC2006-89(2007-1), pp.13-18, 2007.1.31<\/li>\n
          127. \u5c0f\u5c71 \u7167\u592b, \u5f71\u6d66 \u5ce1, \u7af9\u5185 \u5b54\u4e00: \u65e5\u672c\u8a9e\u5c02\u9580\u5206\u91ce\u30c6\u30ad\u30b9\u30c8\u30fc\u30b3\u30fc\u30d1\u30b9\u304b\u3089\u306e\u8907\u5408\u8a9e\u7528\u8a9e\u62bd\u51fa\uff0c \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\uff0c\u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u7814\u7a76\u4f1a\uff0c176-NL-2006, pp.55-50, 2006.11.<\/li>\n
          128. \u4e0b\u6751 \u62d3\u4e5f, \u7af9\u5185 \u5b54\u4e00: \u540d\u8a5e\u306e\u6982\u5ff5\u4f53\u7cfb\u3092\u5229\u7528\u3057\u305f\u898f\u5247\u306b\u57fa\u3065\u304f\u610f\u5473\u5f79\u5272\u4ed8\u4e0e\u30b7\u30b9\u30c6\u30e0\u306e\u69cb\u7bc9\uff0c \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\uff0c\u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u7814\u7a76\u4f1a\uff0c175-NL-2006, pp.13-20, 2006.9.<\/li>\n
          129. \u5e73\u5c3e\u4e00\u6a39, \u7af9\u5185\u5b54\u4e00: \u8907\u5408\u540d\u8a5e\u306b\u7740\u76ee\u3057\u305fWeb\u691c\u7d22\u7d50\u679c\u306e\u30af\u30e9\u30b9\u30bf\u30ea\u30f3\u30b0\uff0c \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\uff0c\u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u7814\u7a76\u4f1a\uff0c175-NL-2006, pp.35-42, 2006.9.<\/li>\n
          130. \u91d1\u5e73\u6602, \u5e73\u5c3e\u4e00\u6a39\uff0c\u7af9\u5185\u5b54\u4e00\uff0c\u5f71\u6d66\u5ce1: \u30a4\u30c7\u30a3\u30aa\u30e0\u306e\u7570\u5f62\u898f\u5247\u3092\u5229\u7528\u3057\u305f\u30a4\u30c7\u30a3\u30aa\u30e0\u691c\u7d22\u30b7\u30b9\u30c6\u30e0\u306e\u69cb\u7bc9\uff0c \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c12\u56de\u5e74\u6b21\u5927\u4f1a\uff0cP6-8, 2006.<\/li>\n
          131. \u91d1\u5e73\u6602, \u8c4a\u5cf6\u5b9f\u548c\uff0c\u7af9\u5185\u5b54\u4e00\uff0c\u5f71\u6d66\u5ce1: \u82f1\u8a9e\u30a4\u30c7\u30a3\u30aa\u30e0\u306e\u7570\u5f62\u3092\u6574\u7406\u3059\u308b\uff0c \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c12\u56de\u5e74\u6b21\u5927\u4f1a\uff0cA5-3, 2006.<\/li>\n
          132. \u5f71\u6d66\u5ce1\uff0c\u4f50\u85e4\u7406\u53f2\uff0c\u7af9\u5185\u5b54\u4e00\uff0c\u5b87\u6d25\u5442\u6b66\u4ec1\uff0c\u8fbb\u6176\u592a\uff0c\u5c0f\u5c71\u7167\u592b: \u7ffb\u8a33\u8005\u652f\u63f4\u306e\u305f\u3081\u306e\u8a00\u8a9e\u30ec\u30d5\u30a1\u30ec\u30f3\u30b9\u30fb\u30c4\u30fc\u30eb\u9ad8\u5ea6\u5316\u65b9\u91dd\uff0c \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c12\u56de\u5e74\u6b21\u5927\u4f1a\uff0cP6-7, 2006<\/li>\n
          133. \u7af9\u5185\u5b54\u4e00\uff0c\u4e7e\u5065\u592a\u90ce\uff0c\u85e4\u7530\u7be4\uff0c\u7af9\u5185\u5948\u592e\uff0c\u963f\u90e8\u4fee\u4e5f: \u5206\u985e\u306e\u6839\u62e0 \u3092\u660e\u793a\u3057\u305f\u52d5\u8a5e\u8a9e\u5f59\u6982\u5ff5\u69cb\u9020\u306e\u69cb\u7bc9, \u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u7814\u7a76\u4f1a\uff0c2005-NL-169, page 123- 130, 2005.<\/li>\n
          134. \u7af9\u5185\u5b54\u4e00: \u8a00\u8a9e\u51e6\u7406\u3092\u610f\u8b58\u3057\u305f\u8a9e\u5f59\u6982\u5ff5\u69cb\u9020\u306e\u69cb\u7bc9, \u6771\u4eac\u5927\u5b66\uff12\uff11\u4e16\u7d00 COE\u300c\u5fc3\u3068\u3053\u3068\u3070\u300d\u30b7\u30f3\u30dd\u30b8\u30a6\u30e0\u300c\u8a9e\u5f59\u6982\u5ff5\u69cb\u9020\u8f9e\u66f8\u306e\u69cb\u7bc9\u3068\u5fdc\u7528\u300d, 2005\u5e743\u670823\u65e5, \u6771\u4eac\u5927\u5b66\u99d2\u5834\u30ad\u30e3\u30f3\u30d1\u30b9, 2005.<\/li>\n
          135. \u6c60\u4e0a\u656c\u660e, \u7af9\u5185\u5b54\u4e00,Web\u4e0a\u306eQA\u30c7\u30fc\u30bf\u306e\u69cb\u9020\u306e\u62bd\u51fa\u3068\u5229\u7528\uff0c \u7b2c11\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a, c2-7, 2005<\/li>\n
          136. \u7af9\u5185\u5b54\u4e00, \u5f71\u6d66\u5ce1, \u30c0\u30a4\u30e6\u30d9\u30a2\u30c8\u30ea\u30b9, \u5c0f\u5c71\u7167\u592b, \u591a\u8a00\u8a9e\u5c02\u9580\u7528\u8a9e\u62bd\u51fa\u30e2\u30c7\u30eb\u306e\u69cb\u7bc9, \u7b2c11\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a, B4-5, 2005<\/li>\n
          137. \u964d\u5e61\u5efa\u592a\u90ce, \u85e4\u7530\u7be4, \u4e7e\u5065\u592a\u90ce, \u677e\u672c\u88d5\u6cbb, \u7af9\u5185 \u5b54\u4e00: \u8a9e\u5f59\u6982\u5ff5\u69cb\u9020\u3092\u7528\u3044\u305f\u6a5f\u80fd\u52d5\u8a5e\u7d50\u5408\u306e\u8a00\u3044\u63db\u3048, \u7b2c10\u56de\u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u5e74\u6b21\u5927\u4f1a, B4-5,2004<\/li>\n
          138. \u7af9\u5185\u5b54\u4e00: \u8a9e\u5f59\u6982\u5ff5\u69cb\u9020\u306b\u3088\u308b\u52d5\u8a5e\u8f9e\u66f8\u306e\u4f5c\u6210, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c10\u56de\u5e74\u6b21\u5927\u4f1a, A5-3, 2004 (\u512a\u79c0\u767a\u8868\u8cde\u53d7\u8cde)<\/li>\n
          139. \u7af9\u5185\u5b54\u4e00, \u5f71\u6d66\u5ce1, \u5c0f\u5c71\u7167\u592b: \u8a9e\u5f59\u6982\u5ff5\u69cb\u9020\u3092\u5229\u7528\u3057\u305f\u300c\u306b\u300d\u306b\u95a2\u3059\u308b\u8907\u5408\u540d\u8a5e\u306e\u5206\u6790, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u7814\u7a76\u4f1a, 2002-NL-150, pp. 133–140, 2002.<\/li>\n
          140. \u7af9\u5185\u5b54\u4e00, \u30b3\u30ea\u30a2\u30fc\u30ca\u30a4\u30b8\u30a7\u30eb: \u751f\u7269\u5b66\u6587\u732e\u304b\u3089\u306e\u5c02\u9580\u7528\u8a9e\u62bd\u51fa\u306b\u304a\u3051\u308b\u6a5f\u68b0\u5b66\u7fd2\u30e2\u30c7\u30eb \u306e\u691c\u8a0e, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u7814\u7a76\u4f1a, 2002-NL-150, pp. 185–190, 2002.<\/li>\n
          141. \u7af9\u5185\u5b54\u4e00: \u8907\u5408\u540d\u8a5e\u89e3\u6790\u30e2\u30c7\u30eb\u306b\u304a\u3051\u308b\u52d5\u8a5e\u306b\u5bfe\u3059\u308b \u8a9e\u5f59\u6982\u5ff5\u69cb\u9020\u306e\u4ed8\u4e0e\u6cd5, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c\uff17\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6, pp. 359–362, 2001.<\/li>\n
          142. \u5ca1\u7530\u771f\u7a42, \u7af9\u5185\u5b54\u4e00, \u5409\u5ca1\u771f\u6cbb, \u5f71\u6d66\u5ce1, \u5c0f\u5c71\u7167\u592b: \u8a9e\u5f59\u306e\u7814\u7a76\u3092\u8003\u616e\u3057\u305f\u5c02\u9580\u7528\u8a9e\u30b3\u30fc\u30d1\u30b9\u306e\u4f5c\u6210, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c\uff17\u56de\u5e74\u6b21\u5927\u4f1a\u767a\u8868\u8ad6\u6587\u96c6, pp. 464–467, 2001.<\/li>\n
          143. K. Takeuchi, K. Uchiyama, M. Yoshioka, K. Kageura, and T. Koyama: Building Japanese Compound Words Analyzer Based on Grammatical Constraint, Proceedings of the First International Symposium on Advanced Informatics, pp. 79–84,Gakushi Kaikan and NACSIS, Tokyo, Japan, (March, 2000).<\/li>\n
          144. \u7af9\u5185\u5b54\u4e00, \u5185\u5c71\u6e05\u5b50, \u5409\u5ca1\u771f\u6cbb, \u5f71\u6d66\u5ce1, \u5c0f\u5c71\u7167\u592b: \u6587\u6cd5\u7684\u5236\u7d04\u3092\u7528\u3044\u305f\u8907\u5408\u8a9e\u89e3\u6790\u30e2\u30c7\u30eb\u306e\u4f5c\u6210, \u5b66\u8853\u60c5\u5831\u30bb\u30f3\u30bf\u30fc\u7d00\u8981,\u7b2c12\u53f7, pp. 7–15, 2000.<\/li>\n
          145. \u7af9\u5185\u5b54\u4e00, \u677e\u672c\u88d5\u6cbb: HMM\u306b\u3088\u308b\u65e5\u672c\u8a9e\u5f62\u614b\u7d20\u89e3\u6790\u30b7\u30b9\u30c6\u30e0\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u63a8\u5b9a, \u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a\u6280\u8853\u7814\u7a76\u5831\u544a\u8a00\u8a9e\u7406\u89e3\u3068\u30b3\u30df\u30e5\u30cb\u30b1\u30fc\u30b7\u30e7\u30f3NLC95-9, pp. 13–19, 1995.<\/li>\n
          146. \u7af9\u5185\u5b54\u4e00, \u5185\u5c71\u6e05\u5b50, \u5409\u5ca1\u771f\u6cbb, \u5f71\u6d66\u5ce1, \u5c0f\u5c71\u7167\u592b: \u8a9e\u5f59\u306e\u5236\u7d04\u3092\u8003\u616e\u3057\u305f\u8907\u5408\u8a9e\u89e3\u6790\u30e2\u30c7\u30eb\u306e\u69cb\u7bc9, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u7814\u7a76\u4f1a, 2000-NL-136, pp. 71–78, 2000.<\/li>\n
          147. K. Uchiyama, K. Takeuchi, M. Yoshioka, K. Kageura, and T. Koyama: Building Japanese Compound Words Analyzer Based on Grammatical Constraint, Proceedings of the First International Symposium on Advanced Informatics, pp. 73–78, Gakushi Kaikan and NACSIS, Tokyo, Japan, (March, 2000).<\/li>\n
          148. K. Takeuchi, M. Yoshioka, T. Koyama, and K. Kageura: Evaluation of the Keyword Extraction Task, Proceedings of the First NTCIR Workshop on Research in Japanese Text Retrieval and Term Recognition, pp. 435–436, KKR Hotel Tokyo, Tokyo, Japan, (August, 1999).<\/li>\n
          149. T. Koyama, M. Yoshioka, K. Takeuchi, and K. Kageura: Evaluation of the Role Analysis Task, Proceedings of the First NTCIR Workshop on Research in Japanese Text Retrieval and Term Recognition, pp. 437–439, KKR Hotel Tokyo, Tokyo, Japan, (August, 1999).<\/li>\n
          150. K. Kageura, M. Yoshioka, K. Tsuji, F. Yoshikane, K. Takeuchi, and T. Koyama: Evaluation of the Term Recognition Task, Proceedings of the First NTCIR Workshop on Research in Japanese Text Retrieval and Term Recognition, pp. 417–434, KKR Hotel Tokyo, Tokyo, Japan, (August, 1999).<\/li>\n
          151. K. Kageura, M. Yoshioka, K. Takeuchi, and T. Koyama: Overview of the TMREC Tasks. Proceedings of the First NTCIR Workshop on Research in Japanese Text Retrieval and Term Recognition, pp. 415–415, KKR Hotel Tokyo, Tokyo, Japan, (August, 1999).<\/li>\n
          152. \u5185\u5c71\u6e05\u5b50, \u7af9\u5185\u5b54\u4e00, \u5409\u5ca1\u771f\u6cbb, \u5f71\u6d66\u5ce1, \u5c0f\u5c71\u7167\u592b: \u5c02\u9580\u5206\u91ce\u306b\u304a\u3051\u308b\u8907\u5408\u540d\u8a5e\u306e\u8a9e\u69cb\u6210\u8981\u7d20\u306e\u54c1\u8a5e\u76f8\u5f53\u30ab\u30c6\u30b4\u30ea\u30fc\u306b\u95a2\u3059\u308b\u4e00\u8003\u5bdf, \u8a00\u8a9e\u51e6\u7406\u5b66\u4f1a\u7b2c5\u56de\u5e74\u6b21\u5927\u4f1a, pp. 341–344, 1999.<\/li>\n
          153. \u5185\u5c71\u6e05\u5b50, \u7af9\u5185\u5b54\u4e00, \u5409\u5ca1\u771f\u6cbb, \u5f71\u6d66\u5ce1, \u5c0f\u5c71\u7167\u592b: \u5c02\u9580\u5206\u91ce\u306b\u304a\u3051\u308b\u8907\u5408\u540d\u8a5e\u306e\u8a9e\u69cb\u6210\u8981\u7d20\u306e\u54c1\u8a5e\u76f8\u5f53, \u30ab\u30c6\u30b4\u30ea\u30fc\u306b\u95a2\u3059\u308b\u4e00\u8003\u5bdf, \u5b66\u8853\u60c5\u5831\u30bb\u30f3\u30bf\u30fc\u7d00\u8981,\u7b2c11\u53f7, pp. 49–57, 1999.<\/li>\n
          154. \u7af9\u5185\u5b54\u4e00, \u5185\u5c71\u6e05\u5b50, \u5409\u5ca1\u771f\u6cbb, \u5f71\u6d66\u5ce1, \u5c0f\u5c71\u7167\u592b: \u8a9e\u57fa\u306e\u8a73\u7d30\u306a\u7279\u5fb4\u3092\u8003\u616e\u3057\u305f\u8907\u5408\u8a9e\u89e3\u6790\u30e2\u30c7\u30eb, \u4fe1\u5b66\u6280\u5831,NLC99-20, pp. 7–14, 1999.<\/li>\n
          155. \u7af9\u5185\u5b54\u4e00, \u677e\u672c\u88d5\u6cbb: \u7d71\u8a08\u7684\u5f62\u614b\u7d20\u89e3\u6790\u3068\u6587\u5b57 N-gram \u3092\u5229\u7528\u3057\u305fOCR\u8aa4\u308a\u8a02\u6b63, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a \u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u7814\u7a76\u4f1aNL130-3, pp. 17–24, 1999.<\/li>\n
          156. \u7af9\u5185\u5b54\u4e00, \u677e\u672c\u88d5\u6cbb: \u5171\u8d77\u60c5\u5831\u3068\u7d71\u8a08\u7684\u5f62\u614b\u7d20\u89e3\u6790\u306b\u3088\u308bOCR\u8aa4\u308a\u8a02\u6b63, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a \u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u7814\u7a76\u4f1aNL121-3, pp. 17–24, 1997.<\/li>\n
          157. \u7af9\u5185\u5b54\u4e00, \u677e\u672c\u88d5\u6cbb: HMM\u3092\u7528\u3044\u305f\u5f62\u614b\u7d20\u89e3\u6790\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u5b66\u7fd2, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u7b2c50\u56de\u5168\u56fd\u5927\u4f1a\u8b1b\u6f14\u8ad6\u6587\u96c63-41, 1995.<\/li>\n
          158. \u7af9\u5185\u5b54\u4e00\uff0c\u677e\u672c\u88d5\u6cbb: HMM\u306b\u3088\u308b\u65e5\u672c\u8a9e\u5f62\u614b\u7d20\u89e3\u6790\u30b7\u30b9\u30c6\u30e0\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u5b66\u7fd2, \u60c5\u5831\u51e6\u7406\u5b66\u4f1a\u81ea\u7136\u8a00\u8a9e\u51e6\u7406\u7814\u7a76\u4f1a, NL-108-3, pp.13-19, 1995. (HMM\u306e\u6559\u5e2b\u7121\u3057\u5b66\u7fd2 (Baum-Welch \u30a2\u30eb\u30b4\u30ea\u30ba\u30e0)\u3092\u65e5\u672c\u8a9e\u5f62\u614b\u7d20\u89e3\u6790\u306b\u9069\u7528\u3057\u3066\u7cbe\u5ea6\u3092\u5411\u4e0a\u3055\u305b\u305f)<\/li>\n<\/ol>\n

            \u535a\u58eb\u8ad6\u6587(Phd thesis)<\/h3>\n